Long-chain diols in settling particles in tropical oceans:insights into sources, seasonality and proxiesMarijke W. de Bar1, Jenny E. Ullgren2, Robert C. Thunnell†, Stuart G. Wakeham3, Geert-Jan A. Brummer4,5,Jan-Berend W. Stuut4,5, Jaap S. Sinninghe Damsté1,6, and Stefan Schouten1,6
1NIOZ Royal Netherlands Institute for Sea Research, Department of Marine Microbiology and Biogeochemistry,and Utrecht University, P.O. Box 59, 1790 AB Den Burg, Texel, the Netherlands2Runde Environmental Centre, Runde, Norway3Skidaway Institute of Oceanography, University of Georgia, 10 Ocean Science Circle, Savannah, USA4NIOZ Royal Netherlands Institute for Sea Research, Department of Ocean Systems, and Utrecht University, P.O. Box 59,1790 AB Den Burg, Texel, the Netherlands5Vrije Universiteit Amsterdam, Faculty of Science, Department of Earth Sciences, De Boelelaan 1085,1081HV Amsterdam, the Netherlands6Department of Earth Sciences, Faculty of Geosciences, Utrecht University, Utrecht, the Netherlands†deceased, 30 July 2018
Received: 16 January 2019 – Discussion started: 1 February 2019Revised: 26 March 2019 – Accepted: 1 April 2019 – Published: 25 April 2019
Abstract. In this study we analyzed sediment trap time se-ries from five tropical sites to assess seasonal variations inconcentrations and fluxes of long-chain diols (LCDs) and as-sociated proxies with emphasis on the long-chain diol index(LDI) temperature proxy. For the tropical Atlantic, we ob-serve that generally less than 2 % of LCDs settling from thewater column are preserved in the sediment. The Atlantic andMozambique Channel traps reveal minimal seasonal varia-tions in the LDI, similar to the two other lipid-based temper-ature proxies TEX86 and UK′
37. In addition, annual mean LDI-derived temperatures are in good agreement with the annualmean satellite-derived sea surface temperatures (SSTs). Incontrast, the LDI in the Cariaco Basin shows larger seasonalvariation, as do the TEX86 and UK′
37. Here, the LDI underesti-mates SST during the warmest months, which is possibly dueto summer stratification and the habitat depth of the diol pro-ducers deepening to around 20–30 m. Surface sediment LDItemperatures in the Atlantic and Mozambique Channel com-pare well with the average LDI-derived temperatures fromthe overlying sediment traps, as well as with decadal an-nual mean SST. Lastly, we observed large seasonal variationsin the diol index, as an indicator of upwelling conditions,at three sites: in the eastern Atlantic, potentially linked to
Guinea Dome upwelling; in the Cariaco Basin, likely causedby seasonal upwelling; and in the Mozambique Channel,where diol index variations may be driven by upwelling fromfavorable winds and/or eddy migration.
1 Introduction
Several proxies exist for the reconstruction of past sea sur-face temperature (SST) based on lipids. The UK′
37 is one of themost commonly applied proxies and is based on the unsatu-ration of long-chain alkenones (LCAs), which are producedby phototrophic haptophyte algae, mainly the cosmopolitanEmiliania huxleyi (Volkman et al., 1980; Brassell et al., 1986;Prahl and Wakeham, 1987; Conte et al., 1994). This indexexhibits a strong positive correlation with SST (Müller et al.,1998; Conte et al., 2006). Another widely used organic pa-leotemperature proxy is the TEX86, as originally proposedby Schouten et al. (2002), based on the relative distributionof archaeal membrane lipids, i.e., glycerol dialkyl glyceroltetraethers (GDGTs), which in the marine realm are mainlythought to be derived from the phylum Thaumarchaeota.Schouten et al. (2002) showed that the TEX86 index mea-
Published by Copernicus Publications on behalf of the European Geosciences Union.
1706 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
sured in marine surface sediments is correlated with SST, andsince then its application in paleoenvironmental studies hasincreased (see, e.g., review by Tierney, 2014). However, re-search has shown that despite their highest abundance beingrecorded in the upper 100 m of the water column, Thaumar-chaeota can be present down to a depth of 5000 m (Karner etal., 2001; Herndl et al., 2005). Accordingly, GDGTs may befound in high concentrations below a depth of 100 m (e.g.,Sinninghe Damsté et al., 2002; Wuchter et al., 2005), andseveral studies have indicated that TEX86 might be morereflective of subsurface temperatures in some regions (e.g.,Huguet et al., 2007; Lopes dos Santos et al., 2010; Kim et al.,2012, 2015; Schouten et al., 2013; Chen et al., 2014; Tierneyet al., 2017; see Zhang and Liu, 2018 for review).
Most recently a SST proxy based on the distribution oflong-chain diols (LCDs), called the long-chain diol index,or LDI has been proposed (Rampen et al., 2012). This in-dex is a ratio of 1,13- and 1,15-diols (i.e., alcohol groupsat position C-1 and C-13 or C-15), and the analysis of glob-ally distributed surface sediments has revealed that this indexstrongly correlates with SST. Since then, the index has beenapplied in several paleoenvironmental studies (e.g., Naafs etal., 2012; Lopes dos Santos et al., 2013; Jonas et al., 2017;Warnock et al., 2018). However, large gaps still remain in theunderstanding of this proxy. The largest uncertainty is thatthe main marine producer of LCDs is unknown. Althoughthese diols have been observed in cultures of certain marineeustigmatophyte algae (e.g., Volkman et al., 1992, 1999; Mé-janelle et al., 2003; Rampen et al., 2014b), the LCD distri-butions in cultures are different from those observed in ma-rine sediments. Furthermore, Balzano et al. (2018) combinedlipid analyses with 18S rRNA gene amplicon sequencing onsuspended particulate matter (SPM) and did not find a sig-nificant direct correlation between LCD concentrations andsequences of known LCD-producers. Rampen et al. (2012)observed the strongest empirical relation between surfacesediment-derived LDI values and SSTs for autumn and sum-mer, suggesting that these are the main growth seasons of thesource organisms. Moreover, the strongest correlation wasalso observed for the upper 20 m of the water column, sug-gesting that the LCDs are likely produced by phototrophicalgae which thrive in the euphotic zone. Nevertheless, LDItemperatures based on surface sediments reflect an integratedsignal of many years, which complicates the interpretation ofthe LDI in terms of seasonal production and depth of exportproduction.
One way of resolving seasonality in the LCD flux and theLDI is to analyze time series samples from sediment trapsthat continuously collect sinking particles in successive timeintervals over periods of a year or more. Such studies havebeen carried out for the UK′
37 as well as for the TEX86 and as-sociated lipids (e.g., Müller and Fischer, 2001; Wuchter et al.,2006; Huguet et al., 2007; Fallet et al., 2011; Yamamoto etal., 2012; Rosell-Melé and Prahl, 2013; Turich et al., 2013).However, very few studies have been undertaken for LCDs.
Villanueva et al. (2014) carried out a sediment trap study inLake Challa (eastern Africa) and Rampen et al. (2008) inthe upwelling region off Somalia. The latter study showedthat 1,14-diols, produced by Proboscia diatoms strongly in-creased early in the upwelling season in contrast to 1,13- and1,15-diols; thus they can be used to trace upwelling. How-ever, neither of these sediment trap studies evaluated the LDI.
In this study, we assess seasonal patterns of the LDI forsediment trap series at five sites: in the Cariaco Basin, in theMozambique Channel and three sites in the tropical NorthAtlantic. During this assessment, we compare the LDI valuesto satellite-derived SST, as well as results obtained for othertemperature proxies, i.e., the TEXH
86 and UK′37. Moreover, for
the Atlantic and Mozambique Channel, we compare the sed-iment trap proxy signals with those preserved in the underly-ing sediments, after settling and burial. Finally, we assess theapplicability of the diol index, based on 1,14-diols producedby Proboscia diatoms (Sinninghe Damsté et al., 2003), as atracer of upwelling and/or productivity in these regions.
2 Materials and methods
2.1 Study sites and sample collection
2.1.1 Tropical North Atlantic
The ocean current and wind patterns of the tropical Atlanticare mostly determined by the seasonal latitudinal shift of theintertropical convergence zone (ITCZ; Fig. 1). The ITCZ mi-grates southward during boreal winter, and northward duringboreal summer. During summer, the southeast trade windsprevail, whereas during winter the northeast trade winds in-tensify. The northeast trade winds drive the North EquatorialCurrent (NEC) which flows westward. South of the NEC,the North Equatorial Countercurrent (NECC) flows towardsthe east (Stramma and Schott, 1999). The South Equato-rial Current (SEC) flows westward and branches off in theNorth Brazil Current (NBC; Stramma and Schott, 1999).When the ITCZ is in the north, the NBC retroflects off theSouth American coast and is carried eastward into the NECC,and thus into the western tropical Atlantic (e.g., Richardsonand Reverdin, 1987). North of the NBC, the Guiana Current(GC) disperses the outflow from the Amazon River towardsthe Caribbean Sea. (Müller-Karger et al., 1988, 1995). How-ever, during boreal summer the NBC may retroflect, carryingthe Amazon River plume far into the western Atlantic (e.g.,Lefèvre et al., 1998; Coles et al., 2013). In fact, every latesummer/autumn, the Amazon River outflow covers around2× 106 km2 of the western North Atlantic, and the river de-livers approximately half of all freshwater input into the trop-ical Atlantic (see Araujo et al., 2017, and references therein).
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1707
Figure 1. (a) Location map showing the five sediment trap mooring sites in the Cariaco Basin, the tropical North Atlantic (M1, M2 andM4) and the Mozambique Channel. Two of the moorings in the tropical North Atlantic (M2 and M4) contain an upper (“U”) and a lower(“L”) trap, shown in the bathymetric section below (b) with traps depicted as red triangles and surface sediments shown as black crosses.A similar section profile is shown for the Mozambique Channel (c), where the sediment trap and the surface sediments are also indicated.All maps/sections were generated using Ocean Data View (Schlitzer, 2015). The approximate seasonal positions of the ITCZ are indicated,in addition to the North Equatorial Current (NEC), the North Equatorial Countercurrent (NECC), the South Equatorial Current (SEC), theMauritania Current (MC), the Guinea Dome (GD), the North Brazil Current (NBC) and the Guiana Current (GC).
The eastern tropical North Atlantic is characterized by up-welling caused by the interaction between the trade windsand the movement of the ITCZ. Cropper et al. (2014) mea-sured upwelling intensity along the northwest African coast-line between 1981 and 2012, in terms of wind speed, SST andother meteorological data. They recognized three latitudi-nal zones: weak permanent annual upwelling north of 26◦ N,strong permanent upwelling between 21 and 26◦ N, and sea-sonal upwelling between 12 and 19◦ N related to the seasonalmigration of the trade winds. Southeast of Cape Verde, large-scale cyclonic circulation forms the Guinea Dome (GD;Fig. 1), which centers around 10◦ N, 22◦W (Mazeika, 1967),i.e., close to mooring site M1. The GD is a thermal upwellingdome, formed by near-surface flow fields associated with thewestward NEC, the eastward NECC and the westward NorthEquatorial Undercurrent (NEUC) (Siedler et al., 1992). Itforms a cyclonic circulation as a result of the eastward flow-ing NECC and the westward flowing NEC (Rossignol andMeyrueis, 1964; Mazeika, 1967). The GD develops from latespring to late fall due to the northern ITCZ position and theresulting Ekman upwelling, but shows significant interannualvariability (Siedler et al., 1992; Yamagata and Iizuka, 1995;Doi et al., 2009) judging from general ocean circulation mod-els. According to Siedler et al. (1992), upwelling is most in-tense between July and October when the ITCZ is in the GDregion and the NECC is strongest.
At three sites, we analyzed five sediment trap series alonga longitudinal transect in the North Atlantic (∼ 12◦ N) to de-termine seasonal variations in the LDI. This transect has beenpreviously studied for Saharan dust deposition in terms ofgrain sizes (van der Does et al., 2016), as the tropical NorthAtlantic receives approximately one-third of the wind-blownSaharan dust (e.g., Duce et al., 1991; Stuut et al., 2005),which might potentially act as fertilizer because of the highiron levels (e.g., Martin and Fitzwater, 1988; Korte et al.,2017; Guerreiro et al., 2017; Goudie and Middleton, 2001,and references therein). Furthermore, Korte et al. (2017) as-sessed mass fluxes and mineralogical composition, Guerreiroet al. (2017) measured coccolith fluxes for two of the time se-ries, and Schreuder et al. (2018a, b) measured long-chain n-alkanes, long-chain n-alkanols and fatty acids, and levoglu-cosan for the same sediment trap samples and surface sedi-ments as analyzed in this study.
At site M1 (12.00◦ N, 23.00◦W), the sediment trap, re-ferred to as M1U, was moored at a water depth of 1150 m(Fig. 1). This mooring is located in the proximity of theGuinea Dome; therefore, it might potentially be influencedby seasonal upwelling. At station M2 (13.81◦ N, 37.82◦W),two sediment traps were recovered, i.e., an “upper” (M2U)trap at a water depth of 1235 m, and a “lower” (M2L) trap ata depth of 3490 m. Lastly, at mooring station M4 (12.06◦ N,49.19◦W), an upper and lower trap series were also recov-
1708 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
ered and analyzed (M4U and M4L), at depths of 1130 and3370 m, respectively. This mooring site may be seasonallyaffected by Amazon River discharge (van der Does et al.,2016; Korte et al., 2017; Guerreiro et al., 2017; Schreuder etal., 2018a). All sediment traps were equipped with 24 sam-pling cups, which sampled synchronously over 16-day inter-vals from October 2012 to November 2013, using HgCl2 asa biocide and borax as a pH buffer to prevent in situ decom-position of the collected material.
2.1.2 Mozambique Channel
The Mozambique Channel is located between Madagascarand Mozambique and is part of the Agulhas Current sys-tem hugging the coast of South Africa (Lutjeharms, 2006).The Agulhas Current system is an important conveyor in thetransport of warm and salty waters from the Indian Oceanto the Atlantic Ocean (Gordon, 1986; Weijer et al., 1999;Peeters et al., 2004). The northern part of the channel isalso influenced by the east African monsoon winds (Biastochand Krauss, 1999; Sætre and da Silva, 1984; Malauene etal., 2014). Between September and March, these winds blowfrom the northeast, parallel to the Mozambique coastline,favoring coastal upwelling. Additionally, the MozambiqueChannel is largely influenced by fast-rotating, mesoscale ed-dies that migrate southward towards the Agulhas region. Us-ing satellite altimetry, Schouten et al. (2003) observed fourto six eddies on average, ca. 300 km in diameter, propagat-ing yearly from the central Mozambique Channel (15◦ S) to-ward the Agulhas area (35◦ S) between 1995 and 2000. Sea-sonal upwelling occurs off northern Mozambique (betweenca. 15 and 18◦ S) (Nehring et al., 1984; Malauene et al.,2014), from August to March with a dominant period ofabout 2 months although periods of 1–4 weeks have alsobeen observed (Malauene et al., 2014).
The sediment trap was moored at 16.8◦ S and 40.8◦ E, ata water depth of 2250 m (Fig. 1; Fallet et al., 2010, 2011)and was the same type as that used for the North Atlantictransect. We analyzed the LCD proxies for two respectivetime intervals: the first interval covered ca. 3.5 years, fromNovember 2003 to September 2007, with a sampling intervalof 21 days. The second interval covered another year, be-tween February 2008 and February 2009, with a samplinginterval of 17 days. Previously, Fallet et al. (2011) publishedforaminiferal, UK′
37 and TEX86 records for the first time inter-val, and the organic carbon content for the follow-up timeseries. For further details on the deployments and sampletreatments, we refer to Fallet et al. (2011, 2012). The twosurface sediments are located across the narrowest transectbetween Mozambique and Madagascar, and were analyzedfor UK′
37 and TEX86 by Fallet et al. (2012) and for LCDs byLattaud et al. (2017b).
2.1.3 Cariaco Basin
The Cariaco Basin is one of the largest marine anoxicbasins (Richards, 1975), located on the continental shelf ofVenezuela. The basin is characterized by permanent strati-fication and is strongly influenced by the migration of theintertropical convergence zone (ITCZ). During late autumnand winter, the ITCZ migrates to the south which resultsin decreased precipitation and trade wind intensificationthat in turn induces upwelling and surface water cooling.This seasonal upwelling is a major source of nutrients thatleads to strong phytoplankton growth along the Venezuelancoast (e.g., Müller-Karger et al., 2001; Thunell et al., 2007).Between August and October, the ITCZ moves northwardagain, resulting in a rainy season and diminishing the tradewinds which inhibits upwelling. During this wet season thecontribution of terrestrially derived nutrients is higher. Due tothe prevalent anoxic conditions in the basin, there is no bio-turbation; this has resulted in the accumulation of laminatedsediments that provide excellent annually to decadally re-solved climate records (e.g., Peterson et al., 1991; Hughen etal., 1996, 1998). Moreover, in November 1995, a time seriesexperiment started to facilitate research on the link betweenbiogeochemistry and the downward flux of particulate ma-terial under anoxic and upwelling conditions (Thunell et al.,2000). This project (CARIACO; http://imars.marine.usf.edu/cariaco, last access: November 2018) involved hydrographiccruises (monthly), water column chemistry measurementsand sediment trap sampling (every 14 days). One mooringcontaining four automated sediment traps (Honjo and Do-herty, 1988) was deployed at 10.50◦ N and 64.67◦W, at a bot-tom depth of around 1400 m. These traps were moored at adepth of 275 m, just above the oxic/anoxic interface (Trap A),at 455 m (Trap B), at 930 m (Trap C) and at 1255 m (Trap D).All traps contained a 13-cup carousel which collected sink-ing particles over 2 weeks, and were serviced every 6 months.For further details on trap deployment and recovery, and sam-ple collection, storage and processing we refer the reader toThunell et al. (2000) and Goñi et al. (2004). In addition tothe sediment trap sampling, the primary productivity of thesurface waters was measured every month using 14C incu-bations (Müller-Karger et al., 2001, 2004). For this study,we investigated two periods, i.e., May 1999–May 2000 andJuly 2002–July 2003 for traps A and B. These years includeupwelling and non-upwelling periods, as well as a disastrousflooding event in December 1999 (Turich et al., 2013). Turichet al. (2013) identified the upwelling periods, linked to themigration of the ITCZ, as indicated by decreasing SST in theCTD (temperature at −1 m water depth) and satellite-basedmeasurements (indicated by grey boxes in Figs. 8 and 10),and shoaling of the average depths of primary production andincreased primary production. Moreover, Turich et al. (2013)evaluated the UK′
37 and TEX86 proxies for the same two timeseries for which we analyzed the LCD proxies.
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1709
2.2 Instrumental data
Satellite SST, precipitation and wind speed time series of theM1, M2 and M4 moorings in the Atlantic derive from Guer-reiro et al. (2017, 2019), who retrieved these data from theOcean Biology Processing Group (OBPG, 2014; Frouin etal., 2003), the Goddard Earth Sciences Data and Informa-tion Services Center (2016) (Huffman et al., 2007; Xie andArkin, 1997) and the NASA Aquarius project (2015a, b) (Leeet al., 2012) (see Supplement of Guerreiro et al., 2017 fordetailed references). The SST and chlorophyll a time seriesdata for the Mozambique Channel were adapted from Fal-let et al. (2011), who retrieved these data from the Giovannidatabase (for details see Fallet et al., 2011). Surface sedimentproxy temperatures were compared to annual mean SST es-timates derived from the World Ocean Atlas (2013) (decadalaverages from 1955 to 2012; Locarnini et al., 2013). Sea sur-face temperature data for the Cariaco Basin were adoptedfrom Turich et al. (2013) and combined with additional CTDtemperatures from the CARIACO time series database fordepths of 2, 5, 10, 15 and 20 m (http://www.imars.usf.edu/CAR/index.html, last access: November 2018; CARIACOtime series composite CTD profiles; lead principal investi-gator: Frank Müller-Karger).
2.3 Lipid extraction
2.3.1 Tropical North Atlantic
The 120 sediment trap samples were sieved through a1 mm mesh wet-split into five aliquots (van der Does etal., 2016), of which one was washed with Milli-Q water,freeze-dried and homogenized for chemical analysis (Ko-rte et al., 2017). For organic geochemistry, sub-aliquots(by weight) were extracted as described by Schreuder etal. (2018a). Briefly, ca. 100 mg dry weight of sediment trapresidue and between 1.5 and 10 g dry weight of surface sed-iment were extracted by ultrasonication using a mixture ofdichloromethane : methanol (DCM/MeOH) (2 : 1; v/v), andwere dried over a Na2SO4 column. For quantification ofLCDs, LCAs and GDGTs, we added the following internalstandards to the total lipid extracts (TLEs): 2.04 µg C22 7,16-diol (Rodrigo-Gamiz et al., 2015), 1.50 µg 10-nonadecanone(C19 : 0 ketone) and 0.1 µg C46 GDGT (Huguet et al., 2006),respectively. Subsequently, the TLEs were separated intoapolar (containing n-alkanes), ketone (containing LCAs)and polar (containing LCDs and GDGTs) fractions overan activated (2 h at 150 ◦C) Al2O3 column by eluting withhexane/DCM (9 : 1; v/v), hexane/DCM (1 : 1; v/v) andDCM/MeOH (1 : 1; v/v), respectively. The apolar fractionswere analyzed by Schreuder et al. (2018a) for n-alkanes. Po-lar fractions were split for GDGT (25 %) and LCD (75 %)analysis. The LCD fraction was silylated by the additionof BSTFA (N ,O-bis(trimethylsilyl)trifluoroacetamide) andpyridine, and were heated at 60 ◦C for 20 min, after which
ethyl acetate was added prior to analysis. The ketone frac-tion was also dissolved in ethyl acetate, and analyzed byGC (gas chromatography) and GC/MS (gas chromatog-raphy mass spectrometry). The GDGT fraction was dis-solved in hexane/isopropanol (99 : 1, v/v), filtered througha 0.45 µm polytetrafluoroethylene (PTFE) filter and analyzedby HPLC-MS (high-performance liquid chromatography –mass spectrometry).
2.3.2 Mozambique Channel
Aliquots of the sediment trap samples from the Mozam-bique Channel were previously extracted and analyzed byFallet et al. (2011) and Fallet et al. (2012), respectively.The sediment trap material was extracted by ultrasonica-tion using a mixture of DCM/MeOH (2 : 1; v/v), dried overNa2SO4, and separated into apolar, ketone and polar frac-tions via alumina pipette column chromatography, by elut-ing with hexane/DCM (9 : 1; v/v), hexane/DCM (1 : 1; v/v)and DCM/MeOH (1 : 1; v/v), respectively. These existingpolar fractions of the sediment trap material were silylated(as described above), dissolved in ethyl acetate and reana-lyzed for LCDs by GC-MS. As no record was kept of thedivision of the extracts and polar fractions into aliquots, wereport the results in relative abundance rather than concentra-tions and fluxes of diols.
2.3.3 Cariaco Basin
Sediment trap material was extracted as described by Turichet al. (2013). Briefly, 1/16 aliquots of the trap samples wereextracted by means of Bligh–Dyer extraction with sonicationusing a phosphate buffer and a trichloroacetic acid (TCA)buffer. The extracts were then separated by adding 5 % NaClin solvent-extracted distilled deionized water, the organicphase was collected, and the aqueous phase was extractedtwice more. The extracts were pooled and dried over Na2SO4and separated by means of Al2O3 column chromatography,eluting with hexane/DCM (9 : 1; v/v), DCM/MeOH (1 : 1;v/v) and MeOH. For this study, the DCM/MeOH (1 : 1; v/v)fraction was silylated (as described above), dissolved in ethylacetate, and analyzed for LCDs using GC-MS. Similar to theMozambique Channel samples, no record was kept of the di-vision of extracts and polar fractions into aliquots; thus, wereport the results in relative abundance.
2.4 Instrumental analysis
2.4.1 GDGTs
The GDGT fractions of the surface sediments and sedimenttraps SPM samples of the tropical North Atlantic were ana-lyzed for GDGTs using ultra-high-performance liquid chro-matography mass spectrometry (UHPLC-MS). We used anAgilent 1260 HPLC, which was equipped with an automaticinjector, interfaced with a 6130 Agilent MSD and HP Chem-
1710 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
Station software according to Hopmans et al. (2016). Com-pound separation was achieved by two silica BEH HILICcolumns in tandem (150 mm× 2.1 mm; 1.7 µm; Waters AC-QUITY) in normal phase, at 25 ◦C. GDGTs were elutedisocratically for 25 min with 82 % A and 18 % B, followedby a linear gradient to 35 % B in 25 min and finally a lin-ear gradient to 100 % B in the last 30 min. “A” denoteshexane; “B” denotes hexane/isopropanol (9 : 1; v/v). Theflow rate was constant at 0.2 mL min−1, and the injectionvolume was 10 µL. The APCI-MS (atmospheric pressurechemical ionization – mass spectrometry) conditions are de-scribed by Hopmans et al. (2016). Detection and quantifi-cation of GDGTs was achieved in selected ion monitoringmode (SIM) mode of the protonated molecules ([M+H]+)of the GDGTs. We used a mixture of crenarchaeol and C46GDGT (internal standard) to assess the relative response fac-tor, which was used for quantification of the GDGTs in thesamples (cf. Huguet et al., 2006).
Sea surface temperatures were calculated by means of theTEXH
86 as defined by Kim et al. (2010), which is a logarithmicfunction of the original TEX86 index (Schouten et al., 2002):
TEXH86 = log
[GDGT−2]+ [GDGT−3]+[Cren′]
[GDGT−1]+ [GDGT−2]+ [GDGT−3]+[Cren′]
, (1)
where the numbers indicate the number of cyclopentane moi-eties of the isoprenoid GDGTs, and Cren′ reflects an isomerof crenarchaeol, i.e., containing a cyclopentane moiety witha cis stereochemistry (Sinninghe Damsté et al., 2018). TheTEXH
86 values were translated to SSTs using the core-top cal-ibration of Kim et al. (2010):
SST= 68.4×TEXH86+ 38.6 (2)
The branched isoprenoid tetraether (BIT) index is a proxyfor the relative contribution of terrestrially derived organiccarbon (Hopmans et al., 2004). We calculated the modifiedversion as reported by de Jonge et al. (2014, 2015) whichis based on the original index as proposed by Hopmans etal. (2004), but includes the 6-methyl brGDGTs:
where the numbers reflect different branched GDGTs (seeHopmans et al., 2004) and Cren reflects crenarchaeol. Thebranched GDGTs were always around the detection limit inthe Atlantic samples, implying a BIT index of around zeroand thus minimal influence of soil organic carbon (Hopmanset al., 2004); therefore, the BIT index is not discussed anyfurther.
2.4.2 LCAs
The ketone fractions of the surface sediments and sedimenttraps samples of the tropical North Atlantic were analyzed
for LCAs on an Agilent 6890N gas chromatograph (GC)with flame ionization detection (FID) after being dissolved inethyl acetate. The GC was equipped with a fused silica col-umn with a length of 50 m, a diameter of 0.32 mm and a coat-ing of CP Sil-5 (film thickness= 0.12 µm). Helium was usedas the carrier gas, and the flow mode was a constant pressureof 100 kPa. The ketone fractions were injected on-columnat a starting temperature of 70 ◦C, which was increased by20 ◦C min−1 to 200 ◦C followed by 3 ◦C min−1 until the fi-nal temperature of 320 ◦C was reached. This end temperaturewas held for 25 min.
The UK′37 index was calculated according to Prahl and
Wakeham (1987):
UK′37 =
[C37 : 2]
[C37 : 2] + [C37 : 3](4)
The UK′37 values were translated to SST following the calibra-
tion of Müller et al. (1998):
SST=UK′
37− 0.0440.033
(5)
We also applied the recently proposed BAYSPLINEBayesian calibration of Tierney and Tingley (2018). Theyand others have shown that the UK′
37 estimates substantially at-tenuate above temperatures of 24 ◦C (e.g., Conte et al., 2001;Goñi et al., 2001; Sicre et al., 2002). The Bayesian calibra-tion moves the upper limit of the UK′
37 calibration from ap-proximately 28 to 29.6 ◦C at unity. As our traps are locatedin tropical regions with SSTs> 24 ◦C, we applied this cali-bration as well.
2.4.3 LCDs
The silylated polar fractions were injected on-column on anAgilent 7890B GC coupled to an Agilent 5977A MS. Thestarting temperature was 70 ◦C, and was increased to 130 ◦Cby 20 ◦C min−1, followed by a linear gradient of 4 ◦C min−1
to an end temperature of 320 ◦C, which was held for 25 min.A total of 1 µL was injected, and separation was achieved ona fused silica column (25× 0.32 mm) coated with CP Sil-5(film thickness 0.12 µm). Helium was used as the carrier gaswith a constant flow of 2 mL min−1. The MS operated withan ionization energy of 70 eV. Identification of LCDs wascarried out in full scan mode, scanning between m/z 50 and850, based on characteristic fragmentation patterns (Volk-man et al., 1992; Versteegh et al., 1997). Proxy calculationsand LCD quantifications were performed via analysis (inSIM mode) of the characteristic fragments (m/z 299, 313,327 and 341; Rampen et al., 2012; m/z 187 for internal diolstandard). For quantification of LCDs in the sediment trapsand seafloor sediments of the tropical Atlantic, the peak areasof the LCDs were corrected for the average relative contribu-tion of the selected SIM fragments to the total ion counts,i.e., 16 % for the saturated LCDs, 9 % for unsaturated LCDsand 25 % for the C22 7,16-diol internal standard.
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1711
Sea surface temperatures were calculated using the LDI,according to Rampen et al. (2012):
LDI=[C30 1,15-diol]
[C28 1,13-diol]+ [C30 1,13-diol]+[C30 1,15-diol]
(6)
These LDI values were converted into SSTs using the fol-lowing equation (Rampen et al., 2012):
SST=LDI− 0.095
0.033(7)
Upwelling conditions were reconstructed using the diol in-dex as proposed by Rampen et al. (2008):
Diol index=[C28 1,14-diol] + [C30 1,14-diol]
[C28 1,14-diol]+[C30 1,14-diol]+ [C30 1,15-diol]
(8)
In 2010, Willmott et al. introduced an alternative diol in-dex, which is defined as the ratio of 1,14-diols over 1,13-diols. As the index of Rampen et al. (2008) includes the C301,15-diol, it can be affected by temperature variation; there-fore, we would normally prefer to use the index of Will-mott et al. (2010). However, we often did not detect theC28 1,13-diol, or it co-eluted with cholest-5-en-7-one-3β-ol,compromising the calculation of the diol index of Willmott etal. (2010). Moreover, the temperature variations in all threesediment traps are minimal as recorded by the LDI. Accord-ingly, we chose to apply the diol index according to Rampenet al. (2008).
Potential fluvial input of organic carbon was determinedby the fractional abundance of the C32 1,15-diol (de Bar etal., 2016; Lattaud et al., 2017a):
The fractional abundance of the C32 1,15-diol was alwayslower than 0.23, suggesting low input of river-derived or-ganic carbon (Lattaud et al., 2017a).
3 Results
3.1 Tropical North Atlantic
We analyzed sediment trap samples from a longitudinal tran-sect (∼ 12◦ N) in the tropical North Atlantic (two uppertraps at a depth of ca. 1200 m, and three lower traps at ca.3500 m; Fig. 1), covering November 2012–November 2013,as well as seven underlying surface sediments, for LCDs,LCAs and GDGTs. Below we present the results for theselipid biomarkers and associated proxies.
3.1.1 LCDs
The LCDs detected in the sediment trap samples and surfacesediments from the tropical North Atlantic (Fig. 2) are the
Figure 2. Relative concentrations of biomarker lipids for the M1,M2 and M4 mooring sites in the tropical North Atlantic. Upper pan-els show the percentages of lipid biomarkers in the lower traps (“L”;3500 m) and the surface sediments (“Sed.”) relative to the annualflux-weighted concentrations in the upper traps (“U”; 1200 m; set at100 %). The lower panel shows the preservation of the individualLCDs (sediments versus upper trap flux-weighted concentration)for the three sediment trap sites. For M1 and M2 the sedimentaryLCD concentrations were based on the average of the two nearbyunderlying surface sediments (Fig. 1). When no bar is shown theLCD was not detected in the surface sediments.
C28, C30 and C30 : 1 1,14- (not in surface sediments), C28 andC30 1,13-, and the C30 1,15-, and C32 1,15-diols. We detectedthe C28 1,14-diol and C29-OH fatty acid in the traps from M1and M4, in a few samples of the M2 traps and in all surfacesediments. For most samples from M2U and M2L, the C281,14-diol was often part of a high background signal, makingidentification and quantification problematic. In these cases,1,14-diol fluxes and the diol index were solely based on the(saturated and monounsaturated) C30 1,14-diol.
The average [1,13+1,15]-diol flux is 2.6(±1.0) µg m−2 d−1 at M1U, 1.4 (±1.2) and 1.2(±1.1) µg m−2 d−1 for M2U and M2L, respectively,
1712 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
and 7.0 (±7.8) and 2.2 (±3.3) µg m−2 d−1 for M4U andM4L, respectively (Fig. 3). The [1,13+1,15]-diol and1,14-diol concentrations in the underlying sediments varybetween 0.05 and 0.50 µg g−1 and between 3 ng g−1 and0.06 µg g−1, respectively. The 1,14-diol flux for M1U aver-ages 0.5 (±0.8) µg m−2 d−1 with a pronounced maximumof 3.5 µg m−2 d−1 in late April (Fig. 5a), irrespective of thetotal mass flux. The average 1,14-diol flux at M2 is muchlower and is similar for the upper and lower traps, beingaround 0.01–0.02 (±0.01) µg m−2 d−1. At M4, the average1,14-diol fluxes are 0.3 (±0.5) and 0.1 (±0.2) µg m−2 d−1
for the upper and lower trap, respectively. There are two ev-ident maxima in the [1,13+1,15]-diols and 1,14-diol fluxesin late April and during October/November, concomitantwith maxima in the total mass flux (Fig. 3d, e). However,in the lower trap this flux maximum is distributed over twosuccessive trap cups, corresponding to late April/early May(Fig. 3e, j).
The LDI ranged between 0.95 and 0.99 in all traps, cor-responding to temperatures of 26.0 to 27.3 ◦C with no par-ticular trends (Fig. 4). For most M2 and M4 samples theC28 1,13-diol was below the quantification limit; hence, LDIwas always around unity, corresponding to 26.9 to 27.3 ◦C(Fig. 4), whereas in other samples the C28 1,13-diol co-elutedwith cholest-5-en-7-one-3β-ol, prohibiting the calculation ofthe LDI and the diol index (Figs. 4, 5). The flux-weightedannual average LDI-derived SSTs were 26.6 ◦C for M1U,and 27.1 ◦C for M2U, M2L, M4U and M4L. The underly-ing sediment was very similar, with LDI values of between0.95 and 0.98 corresponding to 26.0 and 26.9 ◦C (Fig. 6). Thediol index varied from 0.03 to 0.30 in M1U, showing a pro-nounced maximum during spring (Fig. 5a). The diol index atM2 ranged between 0.01 and 0.03 without an evident pattern,whereas the diol index at M4 ranged from 0.01 to 0.10 andshowed the same pattern in the lower and upper trap, with thehighest values during spring (ca. 0.1), followed by a gradualdecrease during summer (Fig. 5e, f).
3.1.2 LCAs
We detected C37, C38 and C39 long-chain alkenones in thesediment trap and surface sediments. The C37 : 3 alkenonewas generally around the limit of quantification for the M2Land M4L traps, and below the limit of quantification forfour out of the seven surface sediment samples, whereas theC37 : 2 alkenone was always sufficiently abundant. The annualmean fluxes of the C37 LCAs were 4.3 (±3.5) µg m−2 d−1
for M1U, 1.2 (±0.9) µg m−2 d−1 and 0.4 (±0.2) µg m−2 d−1
for M2U and M2L, respectively, and 2.9 (±5.1) µg m−2 d−1
and 1.2 (±2.0) µg m−2 d−1 for M4U and M4L, respectively.The concentrations of the C37 LCAs in the underlying sur-face sediments ranged between 0.02 and 0.41 µg g−1. At M4,the two total mass flux peaks at the end of April and dur-ing October/November were also clearly pronounced in theC37 alkenone fluxes (Figs. 3d, e, 5g), as well as the in-
creased signal in the cup reflecting the beginning of May,which followed the cup which recorded the peak in total massflux at the end of April. The UK′
37 varied from 0.87 to 0.93,corresponding to 25.1 to 27.0 ◦C (Fig. 6b) for three out ofseven surface sediments in which the C37 : 3 was above thequantification limit. The flux-weighted average SSTs were26.1 ◦C for M1U, 25.7 and 26.4 ◦C for M2U and M2L, re-spectively, and 28.2 and 27.5 ◦C for M4U and M4L, respec-tively (Fig. 6). SST variations per sediment trap were gener-ally within a 2–3 ◦C range (Fig. 4) with no apparent trends.
3.1.3 GDGTs
The main GDGTs detected were the isoprenoidal GDGT-0, -1, -2, -3, crenarchaeol and the isomer of crenarchaeol.Branched GDGTs were typically around or below quantifi-cation limit. The average iGDGT flux in M1U was 15.5(±4.6) µg m−2 d−1, 2.4 (±1.1) and 2.6 (±0.3) µg m−2 d−1
in M2U and M2L, respectively, and 4.3 (±1.5) and 2.9(±1.2) µg m−2 d−1 in M4U and M4L, respectively (Fig. 3).The surface sediments exhibited iGDGT concentrations be-tween 0.4 and 1.7 µg g−1. Sediment TEXH
86 values varied be-tween 0.62 and 0.69, corresponding to 24.3 to 27.4 ◦C. TheTEXH
86 flux-weighted average SSTs were 25.2 ◦C for M1U,27.3 and 26.6 ◦C for M2U and M2L, respectively, and 27.8and 26.7 ◦C for M4U and M4L, respectively. SSTs typicallyvaried within a range of 1–2 ◦C. At M2U, the TEXH
86 tem-peratures decrease slightly (ca. 1–2 ◦C) between January andJuly (Fig. 4b).
3.2 Mozambique Channel
For two time series (November 2003–September 2007 andFebruary 2008–February 2009), we analyzed LCDs collectedin the sediment trap at a depth of 2250 m as well as nearbyunderlying surface sediments (Fig. 1). The main LCDs ob-served in the sediment traps and surface sediments were theC28 1,12-, 1,13- and 1,14-diols, the C30 1,13-, 1,14- and 1,15-diols, and the C32 1,15-diol. We also observed the C30 : 1 1,14diol in some trap samples, and the C29 12-OH fatty acid in alltrap and sediment samples. In 24 samples, the C28 1,13-diolco-eluted with cholest-5-en-7-one-3β-ol, and thereafter wedid not calculate the LDI for these samples. The C28 1,14-diol was not affected by this cholest-5-en-7-one-3β-ol due toits much higher abundance compared with the C28 1,13-diol;therefore, the diol index was still calculated. The LDI var-ied between 0.94 and 0.99, i.e., close to unity, correspondingto 25.5 to 27.2 ◦C, without an evident trend (Fig. 7a). Thediol index ranged between 0.11 and 0.69, showing substan-tial variation, although not with an evident trend (Fig. 7b).The average LDI-derived temperature of the two underlyingsurface sediments was 26.0 ◦C.
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1713
Figure 3. Lipid biomarker fluxes for the tropical North Atlantic sediment traps, i.e., M1, upper and lower M2, and upper and lower M4 inpanels (a) to (e). Lipid biomarker fluxes (iGDGTs in purple; C37 alkenones in orange; 1,13- and 1,15-diols in black; 1,14-diols in red) areindicated on the left y axis, and the total mass flux (grey stack; Korte et al., 2017) is shown on the right y axis. Lipid biomarker concentrationsare plotted in panels (f) to (j), with biomarker concentrations on the left y axis, and the total mass flux on the right y axis. Note that they axes are different per sediment trap site, but identical for upper (U) and lower (L) traps.
3.3 Cariaco Basin
We analyzed LCDs for two time series (May 1999–May 2000and July 2002–July 2003) from the upper (Trap A; 275 m)and the lower (Trap B; 455 m) trap in the Cariaco Basin. Themain LCDs detected for both time series are the C28 1,14-,C30 1,14-, C30 : 1 1,14-, C28 1,13-, C30 1,15- and C32 1,15-
diols, as well as the C29 12-OH fatty acid. For some sampleswe did not compute the LDI, as the C28 1,13-diol co-elutedwith cholest-5-en-7-one-3β-ol. In a similar fashion to theMozambique Channel, the C28 1,14-diol was not affected bythis co-elution due to its much higher abundance comparedwith the C28 1,13-diol; therefore, the diol index was therefore
1714 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
Figure 4. Temperature proxy records for the tropical North Atlantic. The panels show (a) the upper trap station M1, (b) the upper trap stationM2 and (d) the lower trap M2, respectively, and (c) the upper trap station M4 and (e) lower trap station M4, respectively.
still calculated. The calculated LDI values ranged between24.3 and 25.3 ◦C and 22.0 and 27.2 ◦C for Trap A and Bof the 1999–2000 time series, respectively, with the low-est temperature during winter and the highest during sum-mer. For the 2002–2003 time series, LDI temperatures forTrap A ranged between 23.3 and 26.2 ◦C and between 22.5and 26.5 ◦C for Trap B.
For the May 1999–May 2000 time series, the diol indexvaried between 0.05 and 0.97 for Trap A and between 0.05and 0.91 for Trap B (Fig. 8) with similar trends, i.e., the low-est values of around 0.1–0.2 just before the upwelling pe-riod during November, rapidly increasing towards values be-tween ca. 0.8 and 1 during the upwelling season (Januaryand February). For the time series of July 2002–July 2003,the diol index showed similar trends, i.e., diol index valuesaround 0.8–0.9 during July, which rapidly decrease towardssummer values of around 0.2–0.3. Similar to the 1999–2000time series, the lowest index values (ca. 0.2) are observed justbefore the upwelling period (during September), after whichthey increase towards values of around 0.8–0.9 between De-cember and March at the start of the upwelling season. Atthe end of the upwelling season the diol index increases, fol-lowed by another maximum of around 0.6 during May.
4 Discussion
4.1 LCD sources and seasonality
The 1,14 diols can potentially be derived from two sources:Proboscia diatoms (Sinninghe Damsté et al., 2003; Rampenet al., 2007) or the dictyochophyte Apedinella radians (Ram-pen et al., 2011). The non-detection of the C32 1,14-diol,which is a biomarker for Apedinella radians (Rampen et al.,2011), and the detection of the C30 : 1 1,14 diol and C29 12-OH fatty acid, which are characteristic of Proboscia diatoms(Sinninghe Damsté et al., 2003), suggests that Proboscia di-atoms are most likely the source of 1,14-diols in the tropicalNorth Atlantic, the Mozambique Channel and the CariacoBasin.
In the Cariaco Basin, the diol index shows a strong cor-relation (visually as correlation analysis was not possibledue to differently spaced data in time) with primary produc-tion rates, suggesting that Proboscia productivity was syn-chronous with total productivity (Fig. 8), although for the1999–2000 time series there is a disagreement during Jan-uary/February. Primary productivity in the Cariaco Basin islargely related to seasonal upwelling which occurs betweenNovember and May when the ITCZ is at its southern posi-
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1715
Figure 5. Phytoplankton productivity records for the tropical North Atlantic. Panels (a)–(c) and (e)–(f) show the 1,14-diol fluxes (left y axis;black) and the diol index (right y axis; grey) for the sediment traps. The y axes are the same for these panels. Wind speed and precipitationdata were adapted from Guerreiro et al. (2019); for references regarding remote sensing parameters, see Guerreiro et al. (2017). Panels (d)and (g) show the C37 alkenone fluxes (left y axis; black) and combined fluxes of Emiliania huxleyi and Gephyrocapsa oceanica (fromGuerreiro et al., 2017; right y axis; grey) for the upper traps of M2 and M4.
tion. Hence, the diol index seems to be an excellent indicatorof upwelling intensity in the Cariaco Basin.
The index also shows considerable variation over time inthe Mozambique Channel (Fig. 7b). Previous studies haveshown that upwelling occurs in the Mozambique Channelbetween ca. 15 and 18◦ S (Nehring et al., 1984; Malaueneet al., 2014), i.e., at the location of our sediment trap. Up-welling is reflected by cool water events and slightly en-hanced chlorophyll a levels; Malauene et al. (2014) observedcool water events at ca. 2-month intervals although periodsof 8 to 30 days were also noted. The two main potentialforcing mechanisms for upwelling in the Mozambique Chan-nel are the east African monsoon winds and the mesoscaleeddies migrating through the channel. Fallet et al. (2011)showed that subsurface temperature, current velocity and thedepth of surface-mixed layer all revealed a dominant period-icity of four to six cycles per year, which is the same fre-quency as that of the southward migration of mesoscale ed-
dies in the channel (Harlander et al., 2009; Ridderinkhof etal., 2010), implying that eddy passage strongly influences thewater mass properties. Wavelet analysis of the diol index forthe 2003–2007 period (Fig. S1 in the Supplement) revealedshort periods, occurring around January of 2004, 2005 and2006, of significant (above the 95 % confidence level) vari-ability at about bimonthly frequencies (60-day period). Boththe frequency (bimonthly) and the timing (boreal winter) ofthe observed time periods of the enhanced diol index vari-ability are similar to those of the cool water events as ob-served by Malauene et al. (2014), associated with upwelling(Fig. 7b). The strongest variability of the diol index at aboutbimonthly frequencies occurred in the first half of 2006. Dur-ing the same period, salinity time series showed the passageof several eddies that had a particularly strong effect on theupper layer hydrography (Ullgren et al., 2012). Malaueneet al. (2014) showed that neither upwelling-favorable winds,nor passing eddies, can independently explain the observed
1716 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
Figure 6. Flux-weighted average (annual) proxy results for the sediment traps compared with the underlying sediments (crosses) and annualmean SST (red line; specific for the coordinates of the surface sediments; World Ocean Atlas 2013 1/4◦ grid resolution). Panels (a), (b)and (c) show the LDI, UK′
37 and TEX86 temperature results, respectively. Triangles reflect sediment trap results (red represents upper/∼
1200 m; blue represents lower/∼ 3500 m), and crosses represent surface sediments. In the case of the UK′37 and TEX86, the green and purple
triangles and grey crosses reflect the temperatures calculated using the BAYSPLINE and BAYSPAR models (Tierney and Tingley, 2014,2015, 2018), whereas the other temperatures were calculated using the Müller et al. (1998) and Kim et al. (2010; TEXH
86) calibrations,respectively. Panel (d) shows the flux-weighted average diol index values for the sediment traps and the diol index estimates for the surfacesediments.
Figure 7. The LDI-derived temperatures, in addition to the TEXH86 and UK′
37-derived temperatures and satellite SST (Fallet et al., 2011) (a)and the diol index (b) for the Mozambique Channel sediment trap. The black cross in panel (a) reflects the average LDI temperature of twounderlying surface sediments, with the LDI calibration error. The chlorophyll a data are from Fallet et al. (2011).
upwelling along the northern Mozambique coast. The twoprocesses may act together, and both strongly influence theupper water layer and the organisms living there, potentiallyincluding the LCD producers.
The least (seasonal) variation in the diol index is observedat M2 in the tropical North Atlantic (Fig. 5b, c), which islikely due to its central open ocean position, associated withrelatively stable, oligotrophic conditions (Guerreiro et al.,2017). In contrast, M4 and M1 are closer to the South Amer-
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1717
Figure 8. Seasonal proxy-derived temperature and upwelling/productivity records for the sediment traps in the Cariaco Basin. Panels (a),(b) and (c) show the May 1999–May 2000 time series LDI-, UK′
37- and TEXH86-derived temperature reconstructions for Trap A (depth of
275 m; solid symbols) and Trap B (depth of 455 m; dashed symbols), respectively. Panels (e), (f) and (g) show the proxy data for theJuly 2002–July 2003 time series, with CTD-temperatures (1 m depth) in red. The UK′
37, TEXH86 and CTD temperatures are adopted from
Turich et al. (2013). The horizontal lines reflect the average proxy-derived temperatures (Trap A is denoted using solid lines; Trap B isdenoted using dashed lines). Panels (d) and (h) show the 1,14-diol based diol index (Rampen et al., 2008) for the 1999–2000 and 2002–2003time series, respectively, for Trap A (depth of 275 m; solid symbols) and Trap B (depth of 455 m; dashed symbols). Primary productivity inmg C m−3 h−1 is plotted in green (data adopted from Turich et al., 2013). The shaded area reflects the period of upwelling.
ican and west African coast, respectively, and thus are po-tentially under the influence of Amazon river runoff and up-welling, respectively, and specific wind and ocean circulationregimes (see Sect. 2.1.1). However, at M4, the diol index isalso low (max. 0.1), suggesting low Proboscia productivity(Fig. 5e, f). At M1, in contrast, we observe enhanced val-ues for the diol index of up to ∼ 0.3 during spring (Fig. 5a).
Most likely, an upwelling signal at this location is associ-ated with the seasonal upwelling of the Guinea Dome. Thisupwelling is generally most intense between July and Oc-tober (Siedler et al., 1992), due to the northward movementof the ITCZ and the resulting intensified Ekman upwelling.Specifically, during this period, the trade winds are weaker,atmospheric pressure is lower and the regional wind stress
1718 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
is favorable to upwelling of the North Equatorial Under-current (Voituriez, 1981). Indeed, a decrease in wind speedand increased precipitation from summer to autumn was ob-served (Fig. 5a) which confirms that during these seasonsthe ITCZ was indeed in a northern position, and that during2013 the upwelling associated with the Guinea Dome wasmost favored between July and October. The timing of thediol index peak, i.e., between March and June, is consistentwith previous sediment trap studies elsewhere which haveshown that Proboscia diatoms and 1,14-diols are typicallyfound during pre-upwelling or early upwelling periods (Kon-ing et al., 2001; Smith, 2001; Sinninghe Damsté et al., 2003;Rampen et al., 2007). The surface sediment at 22◦W justeast of M1 also reveals the highest diol index (0.22), likelydue to its closer vicinity to the Guinea Dome center. Severalstudies have reported P. alata diatoms offshore of northwestAfrica (Lange et al., 1998; Treppke et al., 1996; Crosta et al.,2012; Romero et al., 1999), pointing to P. alata as a plausiblesource organism. The sedimentary annual diol indices com-pare well with the sediment trap indices (Fig. 6d), which isconsistent with the results of Rampen et al. (2008). Our re-sults clearly show that the diol index reflects different thingsin different regions. This is due to the ecology of Probosciaspp. where blooms occur during stratification, during earlyupwelling and post-bloom, and from high nutrients to lownutrients (see Rampen et al., 2014a; references in Table 1).Therefore, the type of conditions reflected by the diol indexis specific for every region.
To assess variations in the seasonal production of 1,13-and 1,15-diols in the tropical Atlantic, for which we havethe most complete data set, we calculated the flux-weighted1,13- and 1,15-diol concentrations for the different traps,and summed these per season (Fig. 9). Highest productionis observed in autumn, followed by spring and summer, withthe lowest production during winter (∼ 60 % compared withautumn). This is in agreement with Rampen et al. (2012)who observed, for an extensive set of surface sediments, thestrongest correlation between LDI and SST for autumn, sug-gesting that production of the source organisms of the LDImainly occurs during autumn. At M4, there are two evidentpeaks in the 1,13- and 1,15-diol fluxes at the end of April andOctober 2013. These maxima correlate with peaks in otherlipid biomarker fluxes (i.e., 1,14-diols, C37 alkenones andiGDGTs), total mass flux, calcium carbonate (CaCO3), OM(organic matter) and the residual mass flux which includesthe deposition flux of Saharan dust (Korte et al., 2017). Ac-cording to Guerreiro et al. (2017), the maximum in totalmass flux at the end of April 2013 is likely caused by en-hanced export production due to nutrient enrichment as aresult of wind-forced vertical mixing. The peak at the endof October 2013, is likely associated with discharge fromthe Amazon River. Moreover, both peaks are concomitantwith prominent dust flux maxima, suggesting that Saharandust also acted as nutrient fertilizer (Korte et al., 2017; Guer-reiro et al., 2017). Guirreirro et al. (2017) suggested that dur-
Figure 9. Seasonal summed flux-weighted average of 1,13-/1,15-diol concentrations in all sediment traps (station M1 upper trap, sta-tion M2 upper and lower trap, and station M4 upper and lower trap)of the tropical North Atlantic.
ing the October–November event the Amazon River may notonly have acted as nutrient supplier, but also as buoyant sur-face density retainer of dust-derived nutrients in the surfacewaters, resulting in the development of algal blooms withinjust a few days, potentially explaining the peak 1,13- and1,15-diol fluxes, as well as the peak fluxes of the other lipidbiomarkers. However, they might also partially result fromenhanced particle settling, caused by factors such as dust bal-lasting or faecal pellets of zooplankton (see Guerreiro et al.,2017, and references therein). This agrees with the resultsof Schreuder et al. (2018a) that show that the n-alkane fluxalso peaks concomitantly with the peaks in total mass fluxand biomarkers, whereas n-alkanes are terrestrially derived(predominantly transported by dust); therefore, increased de-position can not result from increased primary productivityin the surface waters.
The C37 alkenone flux at M4U also reveals these two dis-tinct maxima at the end of April and October during 2013(Fig. 5g). Interestingly, this flux, as well as the alkenoneflux at M2U, is consistent with coccolith export fluxes ofthe species Emiliania huxleyi and Gephyrocapsa oceanica(Guerreiro et al., 2017). In fact, when we combine the coc-colith fluxes of both species, we observe strong correlationswith the C37 alkenone fluxes for both M2U and M4U (Fig. 5dand g, respectively; r = 0.77 and 0.92 for M2U and M4U,respectively; p-values< 0.001). This implies that these twospecies are the main LCA producers in the tropical North At-lantic, which agrees with previous findings (e.g., Marlowe etal., 1984; Brassell, 2014; Conte et al., 1994; Volkman et al.,1995).
4.2 Preservation of LCDs
The sediment trap data from the North Atlantic can be usedto assess the relative preservation of LCDs, as well as otherproxy lipid biomarkers, by comparing the flux-weighted con-centration in the traps with the concentrations in the surfacesediments. For all four biomarker groups, i.e., C37 alkenones,iGDGTs, 1,14-diols and 1,13- and 1,15-diols, we observe
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1719
that the flux-weighted concentrations are generally higher inthe upper traps (ca. 1200 m) compared with the lower traps(ca. 3500 m; Fig. 2) by a factor of between 1.2 and 4.4, im-plying degradation during settling down the water column.The concentrations in the surface sediments are 2 to 3 or-ders of magnitude lower (i.e., between 0.1 %–1.5 % of up-per trap signal), implying that degradation of lipids mainlytakes place at the water–sediment surface rather than in thewater column. A similar observation was made for levoglu-cosan in these sediment traps (Schreuder et al., 2018b). Bothare functionalized polar lipids with alcohol groups and thusare chemically relatively similar when compared to speciessuch as fatty acids (carboxyl group) or n-alkanes (no func-tional groups). These degradation rates are likely linked tothe extent of the oxygen exposure time (Hartnett et al., 1998;Hedges et al., 1999) at the seafloor (Hartnett et al., 1998; Sin-ninghe Damsté et al., 2002), as during settling the lipids areexposed to oxygen for weeks, whereas for surface sedimentsthis is typically decades to centuries. Our results comparewell with several other sediment trap studies which showedthat LCDs, LCAs and iGDGTs generally have a preserva-tion factor of around 1 % (surface sediment versus trap) (e.g.,Prahl et al., 2000; Wakeham et al., 2002; Rampen et al., 2007;Yamamoto et al., 2012).
We also identified the C30 and C32 1,15-keto-ol in the At-lantic as well as in the Mozambique and Cariaco sedimenttraps and surface sediments. These lipids are structurally re-lated to LCDs, occur ubiquitously in marine sediments (e.g.,Versteegh et al., 1997, 2000; Bogus et al., 2012; Rampen etal., 2007; Sinninghe Damsté et al., 2003; Wakeham et al.,2002; Jiang et al., 1994) and were inferred to be oxidationproducts of LCDs (Ferreira et al., 2001; Bogus et al., 2012;Sinninghe Damsté et al., 2003). We did not detect 1,14-keto-ols, which supports the hypothesis of Ferreira et al. (2001)and Sinninghe Damsté et al. (2003) that the silica frustulesof Proboscia diatoms sink relatively fast; thus, they are ex-posed to oxygen for a shorter period than the producers of1,13- and 1,15-diols, and are therefore less affected by oxi-dation. Alternatively, the keto-ols are not oxidation productsbut are produced by unknown organisms in the water col-umn. In fact, Méjanelle et al. (2003) observed trace amountsof C30 1,13- and C32 1,15-keto-ols in cultures of the marineeustigmatophyte Nannochloropsis gaditana. Thus, an alter-native explanation for the non-detection of 1,14-keto-ols isthat, in contrast to the 1,15-keto-ols, they were not producedin the water column.
For both the tropical Atlantic and the Cariaco Basin, weobserve highly similar LDI values for the upper and the lowertraps. In the Atlantic there is no statistical difference betweenthe upper and lower traps that are 2200 m apart (two-tailedp > 0.8), but we have insufficient data for the Cariaco Basinfor statistical comparison (Figs. 6a, 8a, e). This suggests thatdegradation in the water column does not affect the LDIproxy. This is in agreement with Reiche et al. (2018) whoperformed a short-term degradation experiment (< 1 year)
and found that the LDI index was not affected by oxic expo-sure on short timescales. However, the oxygen exposure timeon the seafloor is much longer; Rodrigo-Gámiz et al. (2016)showed for sediments in the Arabian Sea (deposited undera range of bottom water oxygen conditions) that differentLCDs had different degradation rates, which compromisedthe LDI ratio. For the three sites in the tropical North At-lantic, we calculated the flux-weighted average proxy valuesfor every sediment trap and compare these with the under-lying surface sediments (Fig. 6a–c). For all indices, i.e., diolindex, LDI, UK′
37 and TEX86, we observe very good corre-spondence between the sediment trap and surface sedimentvalues, implying minimal alteration of the proxies after set-tling and during burial. Similarly, for the Mozambique Chan-nel, the mean diol index and LDI from the sediment trap (i.e.,0.41 and 0.97, respectively) are very similar to the surfacesediment values (i.e., 0.42 and 0.95, respectively). In agree-ment with the consistent diol indices, we observe that all in-dividual LCDs are also preserved relatively equally in thetropical Atlantic (1.2 %–4.3 % at station M1, 0.1 %–2.9 % atstation M2 and 0.03 %–0.16 % at station M4). This contrastswith Rodrigo-Gámiz et al. (2016) who found that the 1,15-diols have the highest degradation rate, followed by the 1,14-and 1,13-diols. Only the C32 1,15-diol seems relatively bet-ter preserved than the other LCDs at all three North Atlanticmooring sites (Fig. 2), suggesting that the C32 1,15-diol isless impacted by degradation. The C32 1,15-diol likely par-tially derives from the same source as the other 1,13- and1,15-diols, but is also produced in fresh water systems (e.g.,Versteegh et al., 1997, 2000; Rampen et al., 2014b; de Baret al., 2016; Lattaud et al., 2017a, b). Hence, the differentpreservation characteristics might be the result of a differentsource for this LCD.
4.3 Relationship between LDI and SST
In the tropical Atlantic and the Mozambique Channel,the LDI-derived SSTs show minimal variability (< 2 ◦C),whereas in the Cariaco Basin we observe much largerchanges that range from 22.0 to 27.2 ◦C (Fig. 8). Both timeseries in the Cariaco Basin show low temperatures betweenNovember and May, associated with the seasonal upwellingand surface water cooling, and significantly higher tempera-tures during the rainy summer. However, during the warmestperiods, the LDI temperatures are generally lower than thosemeasured at the surface by CTD, whereas during the colderphases, the LDI agrees well with the measurements. TheLDI calibration reaches unity at 27.4 ◦C; therefore, is notpossible to resolve the highest temperatures which are be-tween ca. 28 and 30 ◦C. However, the LDI-derived tempera-tures are sometimes well below 27.4 ◦C where the CTD datasuggest SSTs> 28 ◦C. Consequently, the LDI-based temper-atures agree with CTD-based SSTs within calibration er-ror for most of the record, but during summer when theSST is highest, they are offset outside the calibration error
1720 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
(1T ∼ 2.5 ◦C). Interestingly, the UK′37- and TEXH
86-derivedtemperature trends show the same phenomenon (Turich et al.,2013; Fig. 8), where the proxy temperatures are cooler thanthe measured temperatures during the warmer months. How-ever, in contrast to the UK′
37 and LDI, the TEXH86 also over-
estimates the SST during the cold months. For UK′37, Turich
et al. (2013) pointed out that a time lag between synthe-sis, export and deposition could potentially explain the dif-ference between the proxy and CTD temperatures. How-ever, previous analysis of plankton biomass, primary pro-ductivity, bio-optical properties and particulate organic car-bon fluxes for the same time period (Müller-Karger et al.,2004), as well as the total mass and terrigenous fluxes as-sessed by Turich et al. (2013) showed the best correlation atzero-time lag on the basis of their 14-day sample interval.We compared our LDI temperature estimates with monthlyCTD measurements between a depth of 0 and 50 m, the tem-perature at the depth of maximum primary productivity andthe temperature at the chlorophyll maximum (Turich et al.,2013; http://www.imars.usf.edu/cariaco, last access: Novem-ber 2018) (Fig. 10). During the upwelling season, tempera-tures are significantly lower due to the upward migration ofisotherms, whereas during the non-upwelling period, temper-atures are higher, particularly in the upper 20 m, and the wa-ter column is more stratified (Fig. 10). LDI underestimatesthe SST during stratification, which suggests that the LCDproducers may thrive at depths of ca. 20–30 m. During up-welling, LDI temperatures agree better with SST, implyingthat the habitat of the LCD producers is potentially closer tothe surface, coincident with the shoaling of the nutricline andthermocline (Fig. 10). However, these absolute differences inLDI temperatures are generally within the calibration error(2 ◦C); thus, these seasonal variations in LDI temperaturesshould be interpreted with caution. Turich et al. (2003) foundthat the UK′
37-derived temperatures agreed reasonably wellwith the measured temperatures at the chlorophyll maximum,which is generally found below a depth of 20 m (averagedepth of 30–34 m; ranging between 1 and 55 m) in the Cari-aco Basin. The LDI temperatures are almost always higherthan the temperatures at the chlorophyll maximum (Fig. 10),and higher than the temperatures at a depth of 30 m, implyingthat the LDI producers may reside in the upper 30 m of thewater column; this is consistent with the results of Rampen etal. (2012) which showed that LDI-derived temperatures havethe strongest correlation with the temperatures in the upper20 m of the water column. This also agrees with Balzano etal. (2018) who observed the highest LCD abundances withinthe upper 20 m of the water column in the tropical Atlantic.
In the Mozambique Channel, the LDI temperature varia-tions are much smaller (< 2 ◦C; Fig. 7a) than the seasonalSST variation – ranging between ca. 24.5 and 30.5 ◦C. Ac-cordingly, during the warmest months of the year, the differ-ence between LDI-derived and satellite-derived SST is out-side the calibration error (i.e., > 2 ◦C). However, this is sim-
Figure 10. LDI temperature records for the Cariaco Basin time se-ries May 1991–May 2000 and July 2002–July 2003 for Trap A(depth of 275 m; solid symbols) and Trap B (depth of 455 m; dashedsymbols), with CTD-derived temperatures at depths of 2, 10, 20, 30and 50 m (in red; http://www.imars.usf.edu/CAR/index.html, lastaccess: November 2018; CARIACO time series composite CTDprofiles), the temperature at the depth of maximum primary pro-duction (PP maximum; green) and the temperature at the depth ofthe chlorophyll maximum (yellow; data adapted from Turich et al.,2013). The shaded area represents the upwelling season.
ilar to the UK′37 and TEXH
86 which also did not reveal sea-sonal variations. This lack of seasonality was explained bythe lateral advection and resuspension of fine sediment ma-terial by migrating mesoscale eddies which ending up in thedeeply moored sediment trap (Fallet et al., 2011, 2012). Mostlikely, this also explains the lack of seasonal variation in ourLDI record (Fig. 7a). Nevertheless, the average LDI temper-ature for the sediment trap of 26.4 ◦C agrees reasonably wellwith the annual mean satellite-derived SST of 27.6 ◦C for thesampled years. Additionally, there is a good agreement withthe average LDI temperature of 26.0 ◦C for the two under-lying surface sediments, as well as with the decadal aver-age SST of 26.7 ◦C for 1955–2012 (Locarnini et al., 2013)given by the World Ocean Atlas (2013). For the North At-lantic, we also observe rather constant LDI temperatures dur-ing the year (Fig. 4) which contrasts with seasonal variationsin satellite SSTs of ca. 3 to 5 ◦C. Nevertheless, differences
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1721
are mostly within the calibration error, except at M1 and M2where LDI-derived temperatures are between 0.5 and 2.8 ◦Chigher than satellite SSTs during winter and spring. Similarto the LDI, the TEXH
86 and UK′37-derived SSTs for the tropi-
cal Atlantic sediment traps also do not reveal clear seasonalvariation. As all three proxies show minimal seasonal vari-ability, this might indicate that the lipids are potentially al-lochtonous and partially derive from distant regions, result-ing in an integrated average temperature signal, similar tothe Mozambique Channel. Nevertheless, the flux-weightedannual LDI temperatures of the tropical Atlantic sedimenttraps (26.6 for M1 and 27.1 ◦C for M2 and M4) agree wellwith the annual mean satellite-derived SSTs of 26.1, 26.0and 27.5 ◦C for M1, M2 and M4, respectively. Moreover, theLDI-derived temperatures in the underlying sediments (26.5,26.6 and 26.7 ◦C, respectively) do not only agree well withthose found in a single year in the sediment traps, but theyalso agree with the decadal average SSTs for 1955 to 2012(26.2, 27.1 and 26.3 ◦C, respectively; Locarnini et al., 2013;Fig. 6a).
5 Conclusions
In this study we evaluated LCD-based proxies, particularlythe LDI, in sediment trap time series from five sites in thetropical North Atlantic, the Cariaco Basin and the Mozam-bique Channel. For the North Atlantic we found that ca.25 %–85 % of the export of these lipid biomarkers was pre-served during settling from 1200 to 3500 m in the watercolumn, and that generally less than 2 % was preserved inthe surface sediments. Despite substantial degradation at theseafloor, likely linked to the prolonged oxygen exposuretime, LCD-derived temperatures from the sediments are gen-erally very similar to the annual mean LCD-derived tem-peratures in both the deep and shallow traps as well as tothe annual mean SST for the specific sampling year and ondecadal timescales for the specific sites. In the Cariaco Basinwe observe a seasonal signal in the LDI linked to the up-welling season reflecting temperatures of the upper ca. 30 mof the water column. The LDI temperatures in the Mozam-bique Channel and the tropical Atlantic reveal minimal sea-sonal change although the seasonal SST contrasts amount to3–5 ◦C. For the Mozambique Channel this is likely caused bythe lateral advection of resuspended sediment by mesoscaleeddy migration, a signal not substantially altered by diagen-esis. Seasonal variations in the diol index are minimal in thecentral and western North Atlantic and 1,14-diol concentra-tions are rather low, implying little Proboscia diatom produc-tivity. However, in the eastern Atlantic, closest to the Africancontinent, the diol index attains a clear spring maximum thatis likely associated with upwelling in the Guinea Dome dur-ing summer to autumn, suggesting the diol index reflects apre-upwelling signal, consistent with the current knowledgeon Proboscia ecology. In the Cariaco Basin, controlled by
seasonal upwelling, the diol index reveals the same clear sea-sonal trend observed in primary productivity, arguing that thediol index is an excellent indicator of upwelling intensity forthis location.
Data availability. The data reported in this paper are archived usingPANGAEA (https://doi.pangaea.de/10.1594/PANGAEA.898278;de Bar et al., 2019).
Supplement. The supplement related to this article is availableonline at: https://doi.org/10.5194/bg-16-1705-2019-supplement.
Author contributions. MWdB, JSSD and SS designed the experi-ments, and MWdB carried them out. JU carried out the time se-ries analysis. JBWS, GJAB and RCT deployed sediment traps andcollected sediment trap materials. MWdB prepared the paper withcontributions from all coauthors.
Competing interests. The authors declare that they have no conflictof interest.
Acknowledgements. We are grateful to Laura Schreuder andDenise Dorhout for analytical support, Wim Boer for help withMATLAB calculations (BAYSPLINE), Laura Korte and Cata-rina Guerreiro for constructive discussions, and Isla Castañeda, Ul-rike Fallet and Courtney Turich for providing and working up sam-ples. This research was funded by the European Research Coun-cil (ERC) under the European Union’s Seventh Framework Pro-gram (FP7/2007-2013) ERC grant agreement no. 339206 to Ste-fan Schouten and ERC grant agreement no. 311152 as well as NWOproject no. 822.01.008 to Jan-Berend W. Stuut. Stefan Schoutenand Jaap S. Sinninghe Damsté receive financial support from theNetherlands Earth System Science Centre (NESSC) through a grav-itation grant from the Dutch ministry for Education, Culture andScience (grant number 024.002.001).
Review statement. This paper was edited by Markus Kienast andreviewed by two anonymous referees.
References
Araujo, M., Noriega, C., Hounsou-gbo, G. A., Veleda, D., Araujo,J., Bruto, L., Feitosa, F., Flores-Montes, M., Lefevre, N., Melo,P., Otsuka, A., Travassos, K., Schwamborn, R., and Neumann-Leitao, S.: A Synoptic Assessment of the Amazon River-OceanContinuum during Boreal Autumn: From Physics to Plank-ton Communities and Carbon Flux, Front. Microbiol., 8, 1358,https://doi.org/10.3389/fmicb.2017.01358, 2017.
Balzano, S., Lattaud, J., Villanueva, L., Rampen, S. W., Brussaard,C. P. D., van Bleijswijk, J., Bale, N., Sinninghe Damsté, J. S.,and Schouten, S.: A quest for the biological sources of long
1722 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
chain alkyl diols in the western tropical North Atlantic Ocean,Biogeosciences, 15, 5951–5968, https://doi.org/10.5194/bg-15-5951-2018, 2018.
Biastoch, A. and Krauss, W.: The Role of Mesoscale Ed-dies in the Source Regions of the Agulhas Current, J.Phys. Oceanogr., 29, 2303–2317, https://doi.org/10.1175/1520-0485(1999)029<2303:Tromei>2.0.Co;2, 1999.
Bogus, K. A., Zonneveld, K. A. F., Fischer, D., Kasten, S.,Bohrmann, G., and Versteegh, G. J. M.: The effect of meter-scale lateral oxygen gradients at the sediment-water inter-face on selected organic matter based alteration, productiv-ity and temperature proxies, Biogeosciences, 9, 1553–1570,https://doi.org/10.5194/bg-9-1553-2012, 2012.
Brassell, S. C.: Climatic influences on the Paleogene evo-lution of alkenones, Paleoceanography, 29, 255–272,https://doi.org/10.1002/2013pa002576, 2014.
Brassell, S. C., Eglinton, G., Marlowe, I. T., Pflaumann,U., and Sarnthein, M.: Molecular stratigraphy – A newtool for climatic assessment, Nature, 320, 129–133,https://doi.org/10.1038/320129a0, 1986.
Chen, W. W., Mohtadi, M., Schefuss, E., and Mollenhauer, G.:Organic-geochemical proxies of sea surface temperature in sur-face sediments of the tropical eastern Indian Ocean, Deep-SeaRes. Pt. I, 88, 17–29, https://doi.org/10.1016/j.dsr.2014.03.005,2014.
Coles, V. J., Brooks, M. T., Hopkins, J., Stukel, M. R.,Yager, P. L., and Hood, R. R.: The pathways and prop-erties of the Amazon River Plume in the tropical NorthAtlantic Ocean, J. Geophys. Res.-Oceans, 118, 6894–6913,https://doi.org/10.1002/2013jc008981, 2013.
Conte, M. H., Thompson, A., and Eglinton, G.: Primaryproduction of lipid biomarker compounds by EmilianiaHuxleyi – Results from an experimental mesocosm studyin fjords of southwestern Norway, Sarsia, 79, 319–331,https://doi.org/10.1080/00364827.1994.10413564, 1994.
Conte, M. H., Weber, J. C., King, L. L., and Wakeham, S. G.: Thealkenone temperature signal in western North Atlantic surfacewaters, Geochim. Cosmochim. Ac., 65, 4275–4287, 2001.
Conte, M. H., Sicre, M. A., Ruhlemann, C., Weber, J. C., Schulte,S., Schulz-Bull, D., and Blanz, T.: Global temperature calibra-tion of the alkenone unsaturation index UK′
37 in surface waters andcomparison with surface sediments, Geochem. Geophy. Geosy.,7, Q02005, https://doi.org/10.1029/2005GC001054, 2006.
Cropper, T. E., Hanna, E., and Bigg, G. R.: Spatial andtemporal seasonal trends in coastal upwelling off North-west Africa, 1981–2012, Deep-Sea Res. Pt. I, 86, 94–111,https://doi.org/10.1016/j.dsr.2014.01.007, 2014.
Crosta, X., Romero, O. E., Ther, O., and Schneider, R. R.:Climatically-controlled siliceous productivity in the eastern Gulfof Guinea during the last 40 000 yr, Clim. Past, 8, 415–431,https://doi.org/10.5194/cp-8-415-2012, 2012.
de Bar, M. W., Dorhout, D. J. C., Hopmans, E. C., Ram-pen, S. W., Sinninghe Damsté, J. S., and Schouten, S.: Con-straints on the application of long chain diol proxies inthe Iberian Atlantic margin, Org. Geochem., 101, 184–195,https://doi.org/10.1016/j.orggeochem.2016.09.005, 2016.
de Bar, M. W., Ullgren, J., Thunell, R. C., Wakeham, S. G., Brum-mer, G.-J. A., Stuut, J.-B. W., Sinninghe Damsté, J. S., andSchouten, S.: Long chain diols in settling particles in tropi-
cal oceans: insights into sources, seasonality and proxies, PAN-GAEA, https://doi.org/10.1594/PANGAEA.898278, 2019.
de Jonge, C., Hopmans, E. C., Zell, C. I., Kim, J. H., Schouten,S., and Sinninghe Damsté, J. S.: Occurrence and abun-dance of 6-methyl branched glycerol dialkyl glyceroltetraethers in soils: Implications for palaeoclimate re-construction, Geochim. Cosmochim. Ac., 141, 97–112,https://doi.org/10.1016/j.gca.2014.06.013, 2014.
de Jonge, C., Stadnitskaia, A., Hopmans, E. C., Cherkashov,G., Fedotov, A., Streletskaya, I. D., Vasiliev, A. A., andSinninghe Damsté, J. S.: Drastic changes in the distributionof branched tetraether lipids in suspended matter and sedi-ments from the Yenisei River and Kara Sea (Siberia): Im-plications for the use of brGDGT-based proxies in coastalmarine sediments, Geochim. Cosmochim. Ac., 165, 200–225,https://doi.org/10.1016/j.gca.2015.05.044, 2015.
Doi, T., Tozuka, T., and Yamagata, T.: Interannual variabil-ity of the Guinea Dome and its possible link with theAtlantic Meridional Mode, Clim. Dynam., 33, 985–998,https://doi.org/10.1007/s00382-009-0574-z, 2009.
Duce, R. A., Liss, P. S., Merrill, J. T., Atlas, E. L Buat-Menard, P.,Hicks, B. B., Miller, J. M., Prospero, J. M., Arimoto, R., Church,T. M., Ellis, W., Galloway, J. N., Hansen, L., Jickells, T. D.,Knap, A. H., Reinhardt, K. H., Schneider, B., Soudine, A., Tokos,J. J., Tsunogai, S., Wollast, R., and Zhou, M.: The AtmosphericInput of Trace Species to the World Ocean, Global Biogeochem.Cy., 5, 193–259, https://doi.org/10.1029/91gb01778, 1991.
Fallet, U., Brummer, G. J., Zinke, J., Vogels, S., and Ridderinkhof,H.: Contrasting seasonal fluxes of planktonic foraminifera andimpacts on paleothermometry in the Mozambique Channel up-stream of the Agulhas Current, Paleoceanography, 25, PA4223,https://doi.org/10.1029/2010pa001942, 2010.
Fallet, U., Ullgren, J. E., Castaneda, I. S., van Aken, H. M.,Schouten, S., Ridderinkhof, H., and Brummer, G. J. A.: Con-trasting variability in foraminiferal and organic paleotempera-ture proxies in sedimenting particles of the Mozambique Channel(SW Indian Ocean), Geochim. Cosmochim. Ac., 75, 5834–5848,https://doi.org/10.1016/j.gca.2011.08.009, 2011.
Fallet, U., Castaneda, I. S., Aneurin, H. E., Richter, T. O., Boer, W.,Schouten, S., and Brummer, G. J.: Sedimentation and burial oforganic and inorganic temperature proxies in the MozambiqueChannel, SW Indian Ocean, Deep-Sea Res. Pt. I, 59, 37–53,https://doi.org/10.1016/j.dsr.2011.10.002, 2012.
Ferreira, A. M., Miranda, A., Caetano, M., Baas, M., Vale,C., and Sinninghe Damsté, J. S.: Formation of mid-chainalkane keto-ols by post-depositional oxidation of mid-chain di-ols in Mediterranean sapropels, Org. Geochem., 32, 271–276,https://doi.org/10.1016/S0146-6380(00)00181-9, 2001.
Frouin, R., Franz, B. A., and Werdell, P. J.: The SeaWiFS PAR prod-uct, in: Algorithm Updates for the Fourth SeaWiFS Data Repro-cessing, edited by: Hooker, S. B. and Firestone, E. R., NASATech. Memo. 2003–206892, Volume 22, 46–50, The SeaWiFSPAR product, NASA Goddard Space Flight Center, Greenbelt,Maryland, 2003.
Goddard Earth Sciences Data and Information Services Cen-ter: TRMM (TMPA-RT) Near Real-Time Precipitation L3 1day 0.25 degree× 0.25 degree V7, Greenbelt, MD, GoddardEarth Sciences Data and Information Services Center (GESDISC), available at: http://disc.gsfc.nasa.gov/datacollection/
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1723
TRMM_3B42RT_Daily_7.html (last access: 16 April 2019),2016.
Goñi, M. A., Woodworth, M. P., Aceves, H. L., Thunell, R. C.,Tappa, E., Black, D., Müller-Karger, F., Astor, Y., and Varela,R.: Generation, transport, and preservation of the alkenone-basedUK
37 sea surface temperature index in the water column and sed-iments of the Cariaco Basin (Venezuela), Global Biogeochem.Cy., 18, 1–21, https://doi.org/10.1029/2003GB002132, 2004.
Gordon, A. L.: Inter-ocean exchange of thermoclinewater, J. Geophys. Res.-Oceans, 91, 5037–5046,https://doi.org/10.1029/JC091iC04p05037, 1986.
Goudie, A. S. and Middleton, N. J.: Saharan dust storms:nature and consequences, Earth-Sci. Rev., 56, 179–204,https://doi.org/10.1016/S0012-8252(01)00067-8, 2001.
Guerreiro, C. V., Baumann, K.-H., Brummer, G.-J. A., Fischer, G.,Korte, L. F., Merkel, U., Sá, C., de Stigter, H., and Stuut, J.-B.W.: Coccolithophore fluxes in the open tropical North Atlantic:influence of thermocline depth, Amazon water, and Saharan dust,Biogeosciences, 14, 4577–4599, https://doi.org/10.5194/bg-14-4577-2017, 2017.
Guerreiro, C. V., Baumann, K.-H., Brummer, G.-J. A., Fischer, G.,Korte, L. F., Sá, C., and Stuut, J.-B. W.: Wind-forced transatlanticgradients in coccolithophore species fluxes, Prog. Oceanogr., inreview, 2019.
Harlander, U., Ridderinkhof, H., Schouten, M. W., and de Rui-jter, W. P. M.: Long-term observations of transport, eddies, andRossby waves in the Mozambique Channel, J. Geophys. Res.-Oceans, 114, C02003, https://doi.org/10.1029/2008jc004846,2009.
Hartnett, H. E., Keil, R. G., Hedges, J. I., and Devol, A. H.: In-fluence of oxygen exposure time on organic carbon preserva-tion in continental margin sediments, Nature, 391, 572–574,https://doi.org/10.1038/35351, 1998.
Hedges, J. I., Sheng Hu, F., Devol, A. H., Hartnett, H. E., Tsamakis,E., and Keil, R. G.: Sedimentary organic matter preservation: atest for selective degradation under oxic conditions, Am. J. Sci.,299, 529–555, https://doi.org/10.2475/ajs.299.7-9.529 1999.
Herndl, G. J., Reinthaler, T., Teira, E., van Aken, H., Veth,C., Pernthaler, A., and Pernthaler, J.: Contribution ofArchaea to total prokaryotic production in the deep At-lantic Ocean, Appl. Environ. Microb., 71, 2303–2309,https://doi.org/10.1128/aem.71.5.2303-2309.2005, 2005.
Honjo, S. and Doherty, K. W.: Large aperture time-seriessediment traps; design objectives, construction and applica-tion, Deep-Sea Res., 35, 133–149, https://doi.org/10.1016/0198-0149(88)90062-3, 1988.
Hopmans, E. C., Weijers, J. W. H., Schefuß, E., Herfort, L., Sin-ninghe Damsté, J. S., and Schouten, S.: A novel proxy for ter-restrial organic matter in sediments based on branched and iso-prenoid tetraether lipids, Earth Planet. Sc. Lett., 224, 107–116,https://doi.org/10.1016/j.epsl.2004.05.012, 2004.
Hopmans, E. C., Schouten, S., and Sinninghe Damsté,J. S.: The effect of improved chromatography onGDGT-based palaeoproxies, Org. Geochem., 93, 1–6,https://doi.org/10.1016/j.orggeochem.2015.12.006, 2016.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin,E. J., Bowman, K. P., Hong, Y., Stocker, E. F., andWolff, D. B.: The TRMM Multi-satellite Precipitation Anal-ysis: Quasi-Global, Multi-Year, Combined-Sensor Precipita-
tion Estimates at Fine Scale, J. Hydrometeorol., 8, 38–55,https://doi.org/10.1175/JHM560.1, 2007.
Hughen, K. A., Overpeck, J. T., Peterson, L. C., and An-derson, R. F.: The nature of varved sedimentation inthe Cariaco Basin, Venezuela, and its palaeoclimatic sig-nificance, Geol. Soc. Spec. Publ. London, 116, 171–183,https://doi.org/10.1144/gsl.Sp.1996.116.01.15, 1996.
Hughen, K. A., Overpeck, J. T., Lehman, S. J., Kashgar-ian, M., Southon, J., Peterson, L. C., Alley, R., and Sig-man, D. M.: Deglacial changes in ocean circulation froman extended radiocarbon calibration, Nature, 391, 65–68,https://doi.org/10.1038/34150, 1998.
Huguet, C., Hopmans, E. C., Febo-Ayala, W., Thompson, D.H., Sinninghe Damsté, J. S., and Schouten, S.: An improvedmethod to determine the absolute abundance of glycerol dibiphy-tanyl glycerol tetraether lipids, Org. Geochem., 37, 1036–1041,https://doi.org/10.1016/j.orggeochem.2006.05.008, 2006.
Huguet, C., Schimmelmann, A., Thunell, R., Lourens, L. J., Sin-ninghe Damsté, J. S., and Schouten, S.: A study of the TEX86paleothermometer in the water column and sediments of theSanta Barbara Basin, California, Paleoceanography, 22, PA3203,https://doi.org/10.1029/2006pa001310, 2007.
Jiang, S., O’Leary, T., Volkman, J. K., Zhang, H., Jia, R., Yu, S.,Wang, Y., Luan, Z., Sun, Z., and Jiang, R.: Origins and simu-lated thermal alteration of sterols and keto-alcohols in deep-seamarine-sediments of the Okinawa Trough, Org. Geochem., 21,415–422, https://doi.org/10.1016/0146-6380(94)90203-8, 1994.
Jonas, A. S., Schwark, L., and Bauersachs, T.: Late Quaternarywater temperature variations of the Northwest Pacific based onthe lipid paleothermometers TEXH
86, UK′37 and LDI, Deep-Sea
Res. Pt. I, 125, 81–93, https://doi.org/10.1016/j.dsr.2017.04.018,2017.
Karner, M. B., DeLong, E. F., and Karl, D. M.: Archaeal dominancein the mesopelagic zone of the Pacific Ocean, Nature, 409, 507–510, https://doi.org/10.1038/35054051, 2001.
Kim, J.-H., van der Meer, J., Schouten, S., Helmke, P., Willmott, V.,Sangiorgi, F., Koc, N., Hopmans, E. C., and Sinninghe Damsté,J. S.: New indices and calibrations derived from the distributionof crenarchaeal isoprenoid tetraether lipids: Implications for pastsea surface temperature reconstructions, Geochim. Cosmochim.Ac., 74, 4639–4654, https://doi.org/10.1016/j.gca.2010.05.027,2010.
Kim, J.-H., Romero, O. E., Lohmann, G., Donner, B., Laepple, T.,Haam, E., and Sinninghe Damsté, J. S.: Pronounced subsurfacecooling of North Atlantic waters off Northwest Africa duringDansgaard–Oeschger interstadials, Earth Planet. Sc. Lett., 339–340, 95–102, https://doi.org/10.1016/j.epsl.2012.05.018, 2012.
Kim, J.-H., Schouten, S., Rodrigo-Gámiz, M., Rampen, S., Marino,G., Huguet, C., Helmke, P., Buscail, R., Hopmans, E. C.,Pross, J., Sangiorgi, F., Middelburg, J. B. M., and Sin-ninghe Damsté, J. S.: Influence of deep-water derived iso-prenoid tetraether lipids on the TEXH
Koning, E., van Iperen, J. M., van Raaphorst, W., Helder, W., Brum-mer, G.-J. A., and van Weering, T. C. E.: Selective preserva-tion of upwelling-indicating diatoms in sediments off Soma-lia, NW Indian Ocean, Deep-Sea Res. Pt. I, 48, 2473–2495,https://doi.org/10.1016/S0967-0637(01)00019-X, 2001.
1724 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
Korte, L. F., Brummer, G.-J. A., van der Does, M., Guerreiro,C. V., Hennekam, R., van Hateren, J. A., Jong, D., Munday,C. I., Schouten, S., and Stuut, J.-B. W.: Downward particlefluxes of biogenic matter and Saharan dust across the equa-torial North Atlantic, Atmos. Chem. Phys., 17, 6023–6040,https://doi.org/10.5194/acp-17-6023-2017, 2017.
Lange, C. B., Romero, O. E., Wefer, G., and Gabric, A.J.: Offshore influence of coastal upwelling off Mauritania,NW Africa, as recorded by diatoms in sediment traps at2195 m water depth, Deep-Sea Res. Pt. I, 45, 986–1013,https://doi.org/10.1016/s0967-0637(97)00103-9 1998.
Lattaud, J., Kim, J.-H., De Jonge, C., Zell, C., Sinninghe Damsté,J. S., and Schouten, S.: The C32 alkane-1,15-diol as a tracer forriverine input in coastal seas, Geochim. Cosmochim. Ac., 202,146–158, https://doi.org/10.1016/j.gca.2016.12.030, 2017a.
Lattaud, J., Dorhout, D., Schulz, H., Castañeda, I. S., Schefuß, E.,Sinninghe Damsté, J. S., and Schouten, S.: The C32 alkane-1,15-diol as a proxy of late Quaternary riverine input in coastal mar-gins, Clim. Past, 13, 1049–1061, https://doi.org/10.5194/cp-13-1049-2017, 2017b.
Lee, T., Lagerloef, G., Gierach, M. M., Kao, H.-Y., Yueh,S., and Dohan, K.: Aquarius reveals salinity structure oftropical instability waves, Geophys. Res. Lett., 39, L12610,https://doi.org/10.1029/2012GL052232, 2012.
Lefèvre, N., Moore, G., Aiken, J., Watson, A., and Cooper, D.: Vari-ability of pCO2 in the tropical Atlantic in 1995, J. Geophys. Res.,C3, 5623–5634, https://doi.org/10.1029/97JC02303, 1998.
Locarnini, R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P., Gar-cia, H. E., Baranova, O. K., Zweng, M. M., Paver, C. R., Reagan,J. R., Johnson, D. R., Hamilton, M., and Seidov, D.: World OceanAtlas 2013, in: Volume 1: temperature, Technical Ed., NOAA At-las NESDIS 73, 40 pp., Levitus S, Silver Spring, 2013.
Lopes dos Santos, R. A., Prange, M., Castañeda, I. S., Schefuß, E.,Mulitza, S., Schulz, M., Niedermeyer, E. M., Sinninghe Damsté,J. S., and Schouten, S.: Glacial-interglacial variability in Atlanticmeridional overturning circulation and thermocline adjustmentsin the tropical North Atlantic, Earth Planet. Sc. Lett., 300, 407–414, https://doi.org/10.1016/j.epsl.2010.10.030, 2010.
Lopes dos Santos, R. A. L., Spooner, M. I., Barrows, T. T., De Deck-ker, P., Sinninghe Damsté, J. S., and Schouten, S.: Comparison oforganic (UK′
37, TEXH86, LDI) and faunal proxies (foraminiferal as-
semblages) for reconstruction of late Quaternary sea surface tem-perature variability from offshore southeastern Australia, Pale-oceanography, 28, 377–387, https://doi.org/10.1002/palo.20035,2013.
Lutjeharms, J. R. E.: The Agulhas Current, 330 pp., Springer,Berlin, 2006.
Malauene, B. S., Shillington, F. A., Roberts, M. J., andMoloney, C. L.: Cool, elevated chlorophyll-a waters offnorthern Mozambique, Deep-Sea Res. Pt. II, 100, 68–78,https://doi.org/10.1016/j.dsr2.2013.10.017, 2014.
Marlowe, I. T., Green, J. C., Neal, A. C., Brassell, S. C., Eglin-ton, G., and Course, P. A.: Long-Chain (n-C37–C39) alkenones inthe Prymnesiophyceae. Distribution of alkenones and other lipidsand their taxonomic significance, Brit. Phycol. J., 19, 203–216,https://doi.org/10.1080/00071618400650221, 1984.
Martin, J. H. and Fitzwater, S. E.: Iron-deficiency limits phytoplank-ton growth in the Northeast Pacific Subarctic, Nature, 331, 341–343, https://doi.org/10.1038/331341a0, 1988.
Mazeika, P. A.: Thermal domes in the Eastern Tropi-cal Atlantic Ocean, Limnol. Oceanogr., 12, 537–539,https://doi.org/10.4319/lo.1967.12.3.0537, 1967.
Méjanelle, L., Sanchez-Gargallo, A., Bentaleb, I., and Grimalt, J.O.: Long chain n-alkyl diols, hydroxy ketones and sterols in amarine eustigmatophyte, Nannochloropsis gaditana, and in Bra-chionus plicatilis feeding on the algae, Org. Geochem., 34, 527–538, https://doi.org/10.1016/s0146-6380(02)00246-2, 2003.
Müller, P. J. and Fischer, G.: A 4-year sediment trap recordof alkenones from the filamentous upwelling region off CapeBlanc, NW Africa and a comparison with distributions inunderlying sediments, Deep-Sea Res. Pt. I, 48, 1877–1903,https://doi.org/10.1016/S0967-0637(00)00109-6, 2001.
Müller, P. J., Kirst, G., Ruhland, G., von Storch, I., and Rosell-Melé,A.: Calibration of the alkenone paleotemperature index UK′
37based on core-tops from the eastern South Atlantic and the globalocean (60◦ N–60◦ S), Geochim. Cosmochim. Ac., 62, 1757–1772, https://doi.org/10.1016/s0016-7037(98)00097-0, 1998.
Müller-Karger, F. E., McClain, C. R., and Richardson, P. L.:The dispersal of the Amazon’s water, Nature, 333, 56–59,https://doi.org/10.1038/333056a0, 1988.
Müller-Karger, F. E., Richardson, P. L., and McGillicuddy, D.:On the offshore dispersal of the Amazon’s Plume in the NorthAtlantic: Comments on the paper by A. Longhurst, “Seasonalcooling and blooming in tropical oceans”, Deep-Sea Res. Pt. I,42, 2127–2137, https://doi.org/10.1016/0967-0637(95)00085-2,1995.
Müller-Karger, F., Varela, R., Thunell, R., Scranton, M., Bohrer,R., Taylor, G., Capelo, J., Astor, Y., Tappa, E., Ho, T.Y., and Walsh, J. J.: Annual cycle of primary productionin the Cariaco Basin: Response to upwelling and implica-tions for vertical export, J. Geophys. Res., 106, 4527–4542,https://doi.org/10.1029/1999JC000291, 2001.
Müller-Karger, F., Varela, R., Thunell, R., Astor, Y., Zhang, H. Y.,Luerssen, R., and Hu, C. M.: Processes of coastal upwelling andcarbon flux in the Cariaco Basin, Deep-Sea Res. Pt. II, 51, 927–943, https://doi.org/10.1016/j.dsr2.2003.10.010, 2004.
Naafs, B. D. A., Hefter, J., and Stein, R.: Application ofthe long chain diol index (LDI) paleothermometer to theearly Pleistocene (MIS 96), Org. Geochem., 49, 83–85,https://doi.org/10.1016/j.orggeochem.2012.05.011, 2012.
NASA Aquarius project: Aquarius Official Release Level 3 Sea Sur-face Salinity Standard Mapped Image Daily Data V4.0. Ver. 4.0.PO.DAAC, CA, USA, 2015a.
NASA Aquarius project: Aquarius Official Release Level 3 WindSpeed Standard Mapped Image Daily Data V4.0. Ver. 4.0.PO.DAAC, CA, USA, 2015b.
Nehring, D., Hagen, E., Jorge da Silva, A., Schemainda, R., Wolf,G., Michelchen, N., Kaiser, W., Postel, L., Gosselk, F., and Bren-ning, U.: The oceanological conditions in the western part of theMozambique Channel in February–March 1980, Nationalkomi-tee für Geodäsie und Geophysik bei der Akademie der Wis-senschaften der DDR, Potsdam, Germany, 1984.
Peeters, F. J. C., Acheson, R., Brummer, G. J. A., de Ruijter, W.P. M., Schneider, R. R., Ganssen, G. M., Ufkes, E., and Kroon,D.: Vigorous exchange between the Indian and Atlantic oceansat the end of the past five glacial periods, Nature, 430, 661–665,https://doi.org/10.1038/nature02785, 2004.
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1725
Peterson, L. C., Overpeck, J. T., Kipp, N. G., and Imbrie, J.:A high-resolution Late Quaternary upwelling record from theanoxic Cariaco Basin, Venezuela, Paleoceanography, 6, 99–119,https://doi.org/10.1029/90pa02497, 1991.
Prahl, F. G. and Wakeham, S. G.: Calibration of unsat-uration patterns in long-chain ketone compositions forpaleotemperature assessment, Nature, 330, 367–369,https://doi.org/10.1038/330367a0, 1987.
Prahl, F. G., Dymond, J., and Sparrow, M. A.: Annual biomarkerrecord for export production in the central Arabian Sea, Deep-Sea Res. Pt. II, 47, 1581–1604, https://doi.org/10.1016/S0967-0645(99)00155-1, 2000.
Rampen, S. W., Schouten, S., Wakeham, S. G., and SinningheDamsté, J. S.: Seasonal and spatial variation in the sourcesand fluxes of long chain diols and mid-chain hydroxy methylalkanoates in the Arabian Sea, Org. Geochem., 38, 165–179,https://doi.org/10.1016/j.orggeochem.2006.10.008, 2007.
Rampen, S. W., Schouten, S., Koning, E., Brummer, G.-J. A.,and Sinninghe Damsté, J. S.: A 90 kyr upwelling recordfrom the northwestern Indian Ocean using a novel long-chain diol index, Earth Planet. Sc. Lett., 276, 207–213,https://doi.org/10.1016/j.epsl.2008.09.022, 2008.
Rampen, S. W., Schouten, S., and Sinninghe Damsté,J. S.: Occurrence of long chain 1,14-diols inApedinella radians, Org. Geochem., 42, 572–574,https://doi.org/10.1016/j.orggeochem.2011.03.009, 2011.
Rampen, S. W., Willmott, V., Kim, J. H., Uliana, E., Mollenhauer,G., Schefuss, E., Sinninghe Damsté, J. S., and Schouten, S.: Longchain 1,13-and 1,15-diols as a potential proxy for palaeotemper-ature reconstruction, Geochim. Cosmochim. Ac., 84, 204–216,https://doi.org/10.1016/j.gca.2012.01.024, 2012.
Rampen, S. W., Willmott, V., Kim, J. H., Rodrigo-Gámiz,M., Uliana, E., Mollenhauer, G., Schefuss, E., SinningheDamsté, J. S., and Schouten, S.: Evaluation of long chain1,14-alkyl diols in marine sediments as indicators forupwelling and temperature, Org. Geochem., 76, 39–47,https://doi.org/10.1016/j.orggeochem.2014.07.012, 2014a.
Rampen, S. W., Datema, M., Rodrigo-Gámiz, M., Schouten,S., Reichart, G. J., and Sinninghe Damsté, J. S.: Sourcesand proxy potential of long chain alkyl diols in lacus-trine environments, Geochim. Cosmochim. Ac., 144, 59–71,https://doi.org/10.1016/j.gca.2014.08.033, 2014b.
Reiche, S., Rampen, S. W., Dorhout, D. J. C., Sinninghe Damsté,J. S., and Schouten, S.: The impact of oxygen exposure onlong-chain alkyl diols and the long chain diol index (LDI) –a long-term incubation study, Org. Geochem., 124, 238–246,https://doi.org/10.1016/j.orggeochem.2018.08.003, 2018.
Richards, F. A.: The Cariaco Basin (Trench), Oceanogr. Mar. Biol.,13, 11–67, 1975.
Richardson, P. L. and Reverdin, G.: Seasonal cycle of velocity in theAtlantic North Equatorial Countercurrent as measured by surfacedrifters, current meters, and ship drifts, J. Geophys. Res.-Oceans,92, 3691–3708, https://doi.org/10.1029/JC092iC04p03691,1987.
Ridderinkhof, H., van der Werf, P. M., Ullgren, J. E., van Aken, H.M., van Leeuwen, P. J., and de Ruijter, W. P. M.: Seasonal andinterannual variability in the Mozambique Channel from mooredcurrent observations, J. Geophys. Res.-Oceans, 115, C06010,https://doi.org/10.1029/2009jc005619, 2010.
Rodrigo-Gámiz, M., Rampen, S. W., de Haas, H., Baas, M.,Schouten, S., and Sinninghe Damsté, J. S.: Constraints on theapplicability of the organic temperature proxies UK′
37, TEX86 andLDI in the subpolar region around Iceland, Biogeosciences, 12,6573–6590, https://doi.org/10.5194/bg-12-6573-2015, 2015.
Rodrigo-Gámiz, M., Rampen, S. W., Schouten, S., andSinninghe Damsté, J. S.: The impact of oxic degra-dation on long chain alkyl diol distributions in Ara-bian Sea surface sediments, Org. Geochem., 100, 1–9,https://doi.org/10.1016/j.orggeochem.2016.07.003, 2016.
Romero O. E., Lange C. B., Fischer G., Treppke U. F., and WeferG.: Variability in Export Production Documented by DownwardFluxes and Species Composition of Marine Planktic Diatoms:Observations from the Tropical and Equatorial Atlantic, in: Useof Proxies in Paleoceanography, edited by: Fischer, G. and Wefer,G., Springer, Berlin, Heidelberg, 1999.
Rosell-Melé, A. and Prahl, F. G.: Seasonality of UK′37 temperature es-
timates as inferred from sediment trap data, Quaternary Sci. Rev.,72, 128–136, https://doi.org/10.1016/j.quascirev.2013.04.017,2013.
Rossignol, M. and Meyruis, A. M.: Campagnes océanographiquesdu Gérard-Tréca, 53 pp., Cent. Oceanogr. Dakar-Thiaroye,ORSTOM, Dakar, Senegal, 1964.
Sætre, R. and Da Silva, A. J.: The circulation of theMozambique channel, Deep-Sea Res., 31, 485–508,https://doi.org/10.1016/0198-0149(84)90098-0, 1984.
Schlitzer, R.: Data Analysis and Visualization with Ocean DataView, CMOS Bulletin SCMO, 43, 9–13, available at: https://odv.awi.de/ (last access: March 2019), 2015.
Schouten, M. W., de Ruijter, W. P. M., van Leeuwen, P.J., and Ridderinkhof, H.: Eddies and variability in theMozambique Channel, Deep-Sea Res. Pt. II, 50, 1987–2003,https://doi.org/10.1016/s0967-0645(03)00042-0, 2003.
Schouten, S., Hopmans, E. C., Schefuss, E., and SinningheDamsté, J. S.: Distributional variations in marine crenarchaeo-tal membrane lipids: a new tool for reconstructing ancient seawater temperatures?, Earth Planet. Sc. Lett., 204, 265–274,https://doi.org/10.1016/s0012-821x(02)00979-2, 2002.
Schouten, S., Hopmans, E. C., and Sinninghe Damsté, J.S.: The organic geochemistry of glycerol dialkyl glyc-erol tetraether lipids: A review, Org. Geochem., 54, 19–61,https://doi.org/10.1016/j.orggeochem.2012.09.006, 2013.
Schreuder, L. T., Stuut, J.-B. W., Korte, L. F., SinningheDamsté, J. S., and Schouten, S.: Aeolian transport anddeposition of plant wax n-alkanes across the tropicalNorth Atlantic Ocean, Org. Geochem., 115, 113–123,https://doi.org/10.1016/j.orggeochem.2017.10.010, 2018a.
Schreuder, L. T., Hopmans, E. C., Stuut, J.-B. W., SinningheDamsté, J. S., and Schouten, S.: Transport and depositionof the fire biomarker levoglucosan across the tropical NorthAtlantic Ocean, Geochim. Cosmochim. Ac., 227, 171–185,https://doi.org/10.1016/j.gca.2018.02.020, 2018b.
Sicre, M., Bard, E., Ezat, U., and Rostek, F.: Alkenonedistributions in the North Atlantic and Nordic seasurface waters, Geochem. Geophy. Geosy., 3, 1013,https://doi.org/10.1029/2001GC000159, 2002.
Siedler, G., Zangenberg, N., and Onken, R.: Seasonal Changes inthe Tropical Atlantic Circulation – Observation and Simulation
1726 M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans
of the Guinea Dome, J. Geophys. Res.-Oceans, 97, 703–715,https://doi.org/10.1029/91jc02501, 1992.
Sinninghe Damsté, J. S., Rijpstra, W. I. C., Hopmans, E. C.,Prahl, F. G., Wakeham, S. G., and Schouten, S.: Distri-bution of membrane lipids of planktonic Crenarchaeota inthe Arabian seat, Appl. Environ. Microbiol., 68, 2997–3002,https://doi.org/10.1128/aem.68.6.2997-3002.2002, 2002.
Sinninghe Damsté, J. S., Rijpstra, W. I. C., and Reichart, G.-J.:The influence of oxic degradation on the sedimentary biomarkerrecord II. Evidence from Arabian Sea sediments, Geochim. Cos-mochim. Ac., 66, 2737–2754, https://doi.org/10.1016/S0016-7037(02)00865-7, 2002.
Sinninghe Damsté, J. S., Rampen, S., Rijpstra, W. I. C., Abbas, B.,Muyzer, G., and Schouten, S.: A diatomaceous origin for long-chain diols and mid-chain hydroxy methyl alkanoates widelyoccurring in Quaternary marine sediments: Indicators for high-nutrient conditions, Geochim. Cosmochim. Ac., 67, 1339–1348,https://doi.org/10.1016/s0016-7037(02)01225-5, 2003.
Sinninghe Damsté, J. S., Rijpstra, W. I. C., Hopmans, E. C., denUijl, M. J., Weijers, J. W. H., and Schouten, S.: The enigmaticstructure of the crenarchaeol isomer, Org. Geochem., 124, 22–28, https://doi.org/10.1016/j.orggeochem.2018.06.005, 2018.
Smith, S. L.: Understanding the Arabian Sea: Reflections onthe 1994–1996 Arabian Sea Expedition, Deep-Sea Res. Pt. II,48, 1385–1402, https://doi.org/10.1016/S0967-0645(00)00144-2, 2001.
Stramma, L. and Schott, F.: The mean flow field of the trop-ical Atlantic Ocean, Deep-Sea Res. Pt. II, 46, 279–303,https://doi.org/10.1016/s0967-0645(98)00109-x, 1999.
Stuut, J.-B., Zabel, M., Ratmeyer, V., Helmke, P., Schefuß, E.,Lavik, G., and Schneider, R.: Provenance of present-day eoliandust collected off NW Africa, J. Geophys. Res.-Atmos., 110,D04202, https://doi.org/10.1029/2004JD005161, 2005.
Thunell, R., Benitez-Nelson, C., Varela, R., Astor, Y., andMüller-Karger, F.: Particulate organic carbon fluxesalong upwelling-dominated continental margins: Ratesand mechanisms, Global Biogeochem. Cy., 21, GB1022,https://doi.org/10.1029/2006gb002793, 2007.
Thunell, R. C., Varela, R., Llano, M., Collister, J., Müller-Karger, F., and Bohrer, R.: Organic carbon fluxes, degrada-tion, and accumulation in an anoxic basin: Sediment trap re-sults from the Cariaco Basin, Limnol. Oceanogr., 45, 300–308,https://doi.org/10.4319/lo.2000.45.2.0300, 2000.
Tierney, J. E.: 12.14 – Biomarker-Based Inferences of Past Climate:The TEX86 Paleotemperature Proxy A2 – Holland, Heinrich D,in: Treatise on Geochemistry, 2nd Edn., edited by: Turekian, K.K., Elsevier, Oxford, 379–393, 2014.
Tierney, J. E. and Tingley, M. P.: A Bayesian, spatially-varying cal-ibration model for the TEX86 proxy, Geochim. Cosmochim. Ac.,127, 83–106, https://doi.org/10.1016/j.gca.2013.11.026, 2014.
Tierney, J. E. and Tingley, M. P.: A TEX86 surface sedimentdatabase and extended Bayesian calibration, Scientific Data, 2,150029, https://doi.org/10.1038/sdata.2015.29, 2015.
Tierney, J. E. and Tingley, M. P.: BAYSPLINE: A New Calibrationfor the Alkenone Paleothermometer, Paleoceanogr. Paleocl., 33,281–301, https://doi.org/10.1002/2017pa003201, 2018.
Tierney, J. E., Sinninghe Damsté, J. S., Pancost, R. D., Sluijs, A.,and Zachos, J. C.: Eocene temperature gradients, Nat. Geosci.,10, 538–539, https://doi.org/10.1038/ngeo2997, 2017.
Treppke, U. F., Lange, C. B., and Wefer, G.: Vertical fluxes of di-atoms and silicoflagellates in the eastern equatorial Atlantic, andtheir contribution to the sedimentary record, Mar. Micropaleon-tol., 28, 73–96, https://doi.org/10.1016/0377-8398(95)00046-1,1996.
Turich, C., Schouten, S., Thunell, R. C., Varela, R., Astor, Y., andWakeham, S. G.: Comparison of TEX86 and UK′
37 temperatureproxies in sinking particles in the Cariaco Basin, Deep-Sea Res.Pt. I, 78, 115–133, https://doi.org/10.1016/j.dsr.2013.02.008,2013.
Ullgren, J. E., van Aken, H. M., Ridderinkhof, H., and deRuijter, W. P. M.: The hydrography of the MozambiqueChannel from six years of continuous temperature, salinity,and velocity observations, Deep-Sea Res. Pt. I, 69, 36–50,https://doi.org/10.1016/j.dsr.2012.07.003, 2012.
van der Does, M., Korte, L. F., Munday, C. I., Brummer,G.-J. A., and Stuut, J.-B. W.: Particle size traces mod-ern Saharan dust transport and deposition across the equato-rial North Atlantic, Atmos. Chem. Phys., 16, 13697–13710,https://doi.org/10.5194/acp-16-13697-2016, 2016.
Versteegh, G. J. M., Bosch, H. J., and de Leeuw, J. W.: Poten-tial palaeoenvironmental information of C24 to C36 mid-chaindiols, keto-ols and mid-chain hydroxy fatty acids; a critical re-view, Org. Geochem., 27, 1–13, https://doi.org/10.1016/s0146-6380(97)00063-6, 1997.
Versteegh, G. J. M., Jansen, J. H. F., de Leeuw, J. W., andSchneider, R. R.: Mid-chain diols and keto-ols in SE At-lantic sediments: a new tool for tracing past sea surfacewater masses?, Geochim. Cosmochim. Ac., 64, 1879–1892,https://doi.org/10.1016/S0016-7037(99)00398-1, 2000.
Villanueva, L., Besseling, M., Rodrigo-Gámiz, M., Ram-pen, S. W., Verschuren, D., and Sinninghe Damsté, J.S.: Potential biological sources of long chain alkyl di-ols in a lacustrine system, Org. Geochem., 68, 27–30,https://doi.org/10.1016/j.orggeochem.2014.01.001, 2014.
Voituriez, B.: Les sous-courants equatoriaux nord et sud et la forma-tion des dômes thermiques tropicaux, Oceanol. Acta, 4, 497–506,1981.
Volkman, J. K., Eglinton, G., Corner, E. D. S., and Sar-gent, J. R.: Novel unsaturated straight-chain C37-C39 methyland ethyl ketones in marine sediments and a coccol-ithophore Emiliania huxleyi, Phys. Chem. Earth, 12, 219–227,https://doi.org/10.1016/0079-1946(79)90106-X, 1980.
Volkman, J. K., Barrett, S. M., Dunstan, G. A., and Jeffrey, S.W.: C30–C32 alky diols and unsaturated alcohols in microalgaeof the class Eustigmatophyceae, Org. Geochem., 18, 131–138,https://doi.org/10.1016/0146-6380(92)90150-v, 1992.
Volkman, J. K., Barrett, S. M., Blackburn, S. I., and Sikes, E. L.:Alkenones in Gephyrocapsa Oceanica – Implications for stud-ies of paleoclimate, Geochim. Cosmochim. Ac., 59, 513–520,https://doi.org/10.1016/0016-7037(95)00325-t, 1995.
Volkman, J. K., Barrett, S. M., and Blackburn, S. I.: Eu-stigmatophyte microalgae are potential sources of C29sterols, C22–C28 n-alcohols and C28–C32 n-alkyl diolsin freshwater environments, Org. Geochem., 30, 307–318,https://doi.org/10.1016/s0146-6380(99)00009-1, 1999.
Wakeham, S. G., Peterson, M. L., Hedges, J. I., and Lee, C.: Lipidbiomarker fluxes in the Arabian Sea, with a comparison to the
M. W. de Bar et al.: Long-chain diols in settling particles in tropical oceans 1727
equatorial Pacific Ocean, Deep-Sea Res. Pt. II, 49, 2265–2301,https://doi.org/10.1016/S0967-0645(02)00037-1, 2002.
Warnock, J. P., Bauersachs, T., Kotthoff, U., Brandt, H. T., andAndren, E.: Holocene environmental history of the Anger-manalven Estuary, northern Baltic Sea, Boreas, 47, 593–608,https://doi.org/10.1111/bor.12281, 2018.
Weijer, W., de Ruiter, W. P. M., Dijkstra, H. A., andvan Leeuwen, P. J.: Impact of interbasin exchangeon the Atlantic overturning circulation, J. Phys.Oceanogr., 29, 2266–2284, https://doi.org/10.1175/1520-0485(1999)029<2266:Ioieot>2.0.Co;2, 1999.
Willmott, V., Rampen, S. W., Domack, E., Canals, M., Sin-ninghe Damsté, J. S., and Schouten, S.: Holocene changesin Proboscia diatom productivity in shelf waters of thenorth-western Antarctic Peninsula, Antarct. Sci., 22, 3–10,https://doi.org/10.1017/s095410200999037x, 2010.
Wuchter, C., Schouten, S., Wakeham, S. G., and Sinninghe Damsté,J. S.: Temporal and spatial variation in tetraether membranelipids of marine Crenarchaeota in particulate organic matter: Im-plications for TEX86 paleothermometry, Paleoceanography, 20,PA3013, https://doi.org/10.1029/2004pa001110, 2005.
Wuchter, C., Schouten, S., Wakeham, S. G., and SinningheDamsté, J. S.: Archaeal tetraether membrane lipid fluxes inthe northeastern Pacific and the Arabian Sea: Implicationsfor TEX86 paleothermometry, Paleoceanography, 21, PA4208,https://doi.org/10.1029/2006PA001279, 2006.
Xie, P. and Arkin, P. A.: Global precipitation: A 17-yearmonthly analysis based on gauge observations, satelliteestimates, and numerical model outputs, B. Am. Mete-orol. Soc., 78, 2539–2558, https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2, 1997.
Yamagata, T. and Iizuka, S.: Simulation of the TropicalThermal Domes in the Atlantic – A Seasonal Cycle, J.Phys. Oceanogr., 25, 2129–2140, https://doi.org/10.1175/1520-0485(1995)025<2129:Sotttd>2.0.Co;2, 1995.
Yamamoto, M., Shimamoto, A., Fukuhara, T., Tanaka, Y.,and Ishizaka, J.: Glycerol dialkyl glycerol tetraethersand TEX86 index in sinking particles in the west-ern North Pacific, Org. Geochem., 53, 52–62,https://doi.org/10.1016/j.orggeochem.2012.04.010, 2012.
Zhang, Y. G. and Liu, X. Q.: Export Depth of theTEX86 Signal, Paleoceanogr. Paleocl., 33, 666–671,https://doi.org/10.1029/2018PA003337, 2018.
